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A Brief History of Species Distribution Modeling: Bibliometric Study on the Web of Science

Year 2024, Volume: 20 Issue: 2, 334 - 351, 28.12.2024
https://doi.org/10.58816/duzceod.1523682

Abstract

This study examines the historical evolution and potential future developments of species distribution modeling (SDM). The origins of SDMs can be traced back to Humboldt's work on plant geography and Darwin's contributions to the theory of evolution. Since the 1980s, particularly with the advancement of data analytics and statistical methods, SDMs have become a significant tool in ecological and biogeographical research. The study analyzes data from the Web of Science Core Collection for the years 1980-2024 using bibliometric methods. The analysis, conducted with the "bibliometrix" package in the R programming language, assesses the evolution of SDMs over time and the changes in methodologies used. The findings indicate that SDMs have a wide range of applications and are increasingly utilized in the context of climate change. Additionally, advancements in statistics and computer technologies are believed to have paved the way for the development of various SDM approaches.

References

  • Acarer, A. (2024). Role of Climate Change on Oriental Spruce (Picea orientalis L.): Modeling and Mapping. BioResources, 19(2), 3845-3856.
  • Acarer, A., & Mert, A. (2024). 21st Century Climate Change Threatens on the Brown Bear. Cerne, 30, e-103305.
  • Aria, M. & Cuccurullo, C. (2017) bibliometrix: An R-tool for comprehensive science mapping analysis, Journal of Informetrics, 11(4), pp 959-975, Elsevier.
  • Beram, A. (2024). Bibliometric Analysis of Academic Studies on Particleboard. Düzce Üniversitesi Orman Fakültesi Ormancılık Dergisi, 20(1), 395-412.
  • Berk, Ş., Özdemir, S., & Pektaş, A. N. (2024). Visualization of scientific production in Caenorhabditis elegans: a bibliometric analysis (1980–2023). Genomics and Informatics, 22(1), 1-15.
  • Chala, D., Roos, C., Svenning, J. C., & Zinner, D. (2019). Species-specific effects of climate change on the distribution of suitable baboon habitats–Ecological niche modeling of current and Last Glacial Maximum conditions. Journal of Human Evolution, 132, 215-226.
  • Çıvğa, A. (2023). Sütçüler Kekiği (Origanum minutiflorum) Potansiyel Dağılım Modellemesi. 21. Yüzyılda Fen ve Teknik, 10(19), 1-8.
  • Çıvğa, A., Özdemir, S., & Gülsoy, S. (2024). Prediction of potential geographic distribution of Capparis spinosa. Biological Diversity and Conservation, 17(3), 206-215.
  • Darwin, C. (1859). The origin of species by means of natural selection. London: Murray. Reedited by E Mayr.
  • Engler, R. & Guisan, A. (2009). MigClim: predicting plant distribution and dispersal in a changing climate. Diversity and distributions, 15(4), 590-601.
  • Ertuğrul, E. T., Mert, A., & Oğurlu, İ. (2017). Burdur Gölü Havzasında bazı yaban hayvanlarının habitat uygunluk haritalaması. Türkiye Ormancılık Dergisi, 18(2), 149-154.
  • Galdıni, S., Silva, R., Zolin, C., Tosto, S., Quartaroli, C., Pereıra, L., & Gomes, M. (2023). InVEST-Integrated Valuation of Ecosystem Services and Tradeoffs.
  • Guisan, A., & Zimmermann, N. E. (2000). Predictive habitat distribution models in ecology. Ecological modelling, 135(2-3), 147-186.
  • Hajima, T., Kawamiya, M., Watanabe, M., Kato, E., Tachiiri, K., Sugiyama, M., & Ito, A. (2014). Modeling in Earth system science up to and beyond IPCC AR5. Progress in Earth and Planetary Science, 1, 1-25.
  • Keith, D. A., Elith, J., & Simpson, C. C. (2014). Predicting distribution changes of a mire ecosystem under future climates. Diversity and Distributions, 20(4), 440-454.
  • Özdemir, S. (2022). ‘Batı Akdeniz'de iklim değişimine göre asli orman ağacı türlerinin dağılım modellemesi’. Doktora Tezi, Isparta Uygulamalı Bilimler Üniversitesi, Lisansüstü Eğitim Enstitüsü, Isparta.
  • Özdemir, S. (2024). Testing the Effect of Resolution on Species Distribution Models Using Two Invasive Species. Polish Journal of Environmental Studies, 33(2), 1325-1335.
  • Özdemir, S., Gülsoy, S., & Mert, A. (2020a). Predicting the effect of climate change on the potential distribution of Crimean Juniper. Kastamonu University Journal of Forestry Faculty, 20(2), 133-142.
  • Özdemir, S., Özkan, K., & Mert, A. (2020b). An ecological perspective on climate change scenarios. Biological Diversity and Conservation, 13(3), 361-371.
  • Peterson, A. T., Ortega-Huerta, M. A., Bartley, J., Sánchez-Cordero, V., Soberón, J., Buddemeier, R. H., & Stockwell, D. R. (2002). Future projections for Mexican faunas under global climate change scenarios. Nature, 416(6881), 626-629.
  • R Core Team (2021). RA language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing, https://www.R-project.org/.
  • Sharp, R., Tallis, H. T., Ricketts, T., Guerry, A. D., Wood, S. A., Chaplin-Kramer, R., & Douglass, J. (2016). Invest.-Integrated Valuation of Ecosystem Services and Tradeoffs. Project, TNC; University, S.; Minnesota, U. o.
  • Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K., & Miller, H. (2007). IPCC fourth assessment report (AR4). Climate change, 374.
  • Spalding, V.M. (1890). The distribution of plants. The American Naturalist, 24(285), 819-831.
  • Thuiller, W. (2004). Patterns and uncertainties of species' range shifts under climate change. Global change biology, 10(12), 2020-2027.
  • Valavi, R., Elith, J., Lahoz‐Monfort, J. J., & Guillera‐Arroita, G. (2021). Modelling species presence‐only data with random forests. Ecography, 44(12), 1731-1742.
  • Von Humboldt, A. (1814) Essay on the geography of plants. Chicago: Foundations ofbiogeography: classic papers with commentaries. University of Chicago Press.
  • Zaniewski, A. E., Lehmann, A., & Overton, J. M. (2002). Predicting species spatial distributions using presence-only data: a case study of native New Zealand ferns. Ecological modelling, 157(2-3), 261-280.
  • Zenbilci, M., Özdemir, S., Çıvğa, A., Ünal, Y., & Oğurlu, İ. (2024). Habitat suitability modeling of wild goat (Capra aegagrus Erxleben, 1777) in different periods. Šumarski list, 148(5-6), 273-284.

Tür Dağılım Modellemesinin Kısa Tarihi: Web of Science üzerinden Bibliyometrik Çalışma

Year 2024, Volume: 20 Issue: 2, 334 - 351, 28.12.2024
https://doi.org/10.58816/duzceod.1523682

Abstract

Bu çalışmada tür dağılım modellemelerinin (TDM) tarihsel evrimi ve gelecekteki potansiyel gelişmeleri incelenmiştir. TDM'lerin kökeni, Humboldt'un bitki coğrafyası çalışmalarına ve Darwin'in türlerin evrimi üzerine yaptığı katkılara dayanır. 1980'lerden itibaren, özellikle veri analitiği ve istatistiksel yöntemlerin gelişmesiyle, TDM'ler ekoloji ve biyocoğrafya araştırmalarda önemli bir araç haline gelmiştir. Çalışmada, Web of Science Core Collection veri tabanından 1980-2024 yıllarına ait olarak elde edilen veriler bibliyometrik yöntemlerle analiz edilmiştir. R programlama dilinde "bibliometrix" paketi kullanılarak yapılan analizlerle, TDM'lerin zaman içindeki gelişimi, kullanılan yöntemlerdeki değişimler değerlendirilmiştir. Bulgular, TDM'lerin geniş bir uygulama alanına sahip olduğunu, iklim değişikliği ile beraber giderek daha fazla kullanıldığını ortaya koymuştur. Ayrıca istatistik ve bilgisayar teknolojileri alanlarındaki gelişmelerinde de farklı TDM yaklaşımlarının geliştirilmesine zemin hazırladığı düşünülmektedir.

References

  • Acarer, A. (2024). Role of Climate Change on Oriental Spruce (Picea orientalis L.): Modeling and Mapping. BioResources, 19(2), 3845-3856.
  • Acarer, A., & Mert, A. (2024). 21st Century Climate Change Threatens on the Brown Bear. Cerne, 30, e-103305.
  • Aria, M. & Cuccurullo, C. (2017) bibliometrix: An R-tool for comprehensive science mapping analysis, Journal of Informetrics, 11(4), pp 959-975, Elsevier.
  • Beram, A. (2024). Bibliometric Analysis of Academic Studies on Particleboard. Düzce Üniversitesi Orman Fakültesi Ormancılık Dergisi, 20(1), 395-412.
  • Berk, Ş., Özdemir, S., & Pektaş, A. N. (2024). Visualization of scientific production in Caenorhabditis elegans: a bibliometric analysis (1980–2023). Genomics and Informatics, 22(1), 1-15.
  • Chala, D., Roos, C., Svenning, J. C., & Zinner, D. (2019). Species-specific effects of climate change on the distribution of suitable baboon habitats–Ecological niche modeling of current and Last Glacial Maximum conditions. Journal of Human Evolution, 132, 215-226.
  • Çıvğa, A. (2023). Sütçüler Kekiği (Origanum minutiflorum) Potansiyel Dağılım Modellemesi. 21. Yüzyılda Fen ve Teknik, 10(19), 1-8.
  • Çıvğa, A., Özdemir, S., & Gülsoy, S. (2024). Prediction of potential geographic distribution of Capparis spinosa. Biological Diversity and Conservation, 17(3), 206-215.
  • Darwin, C. (1859). The origin of species by means of natural selection. London: Murray. Reedited by E Mayr.
  • Engler, R. & Guisan, A. (2009). MigClim: predicting plant distribution and dispersal in a changing climate. Diversity and distributions, 15(4), 590-601.
  • Ertuğrul, E. T., Mert, A., & Oğurlu, İ. (2017). Burdur Gölü Havzasında bazı yaban hayvanlarının habitat uygunluk haritalaması. Türkiye Ormancılık Dergisi, 18(2), 149-154.
  • Galdıni, S., Silva, R., Zolin, C., Tosto, S., Quartaroli, C., Pereıra, L., & Gomes, M. (2023). InVEST-Integrated Valuation of Ecosystem Services and Tradeoffs.
  • Guisan, A., & Zimmermann, N. E. (2000). Predictive habitat distribution models in ecology. Ecological modelling, 135(2-3), 147-186.
  • Hajima, T., Kawamiya, M., Watanabe, M., Kato, E., Tachiiri, K., Sugiyama, M., & Ito, A. (2014). Modeling in Earth system science up to and beyond IPCC AR5. Progress in Earth and Planetary Science, 1, 1-25.
  • Keith, D. A., Elith, J., & Simpson, C. C. (2014). Predicting distribution changes of a mire ecosystem under future climates. Diversity and Distributions, 20(4), 440-454.
  • Özdemir, S. (2022). ‘Batı Akdeniz'de iklim değişimine göre asli orman ağacı türlerinin dağılım modellemesi’. Doktora Tezi, Isparta Uygulamalı Bilimler Üniversitesi, Lisansüstü Eğitim Enstitüsü, Isparta.
  • Özdemir, S. (2024). Testing the Effect of Resolution on Species Distribution Models Using Two Invasive Species. Polish Journal of Environmental Studies, 33(2), 1325-1335.
  • Özdemir, S., Gülsoy, S., & Mert, A. (2020a). Predicting the effect of climate change on the potential distribution of Crimean Juniper. Kastamonu University Journal of Forestry Faculty, 20(2), 133-142.
  • Özdemir, S., Özkan, K., & Mert, A. (2020b). An ecological perspective on climate change scenarios. Biological Diversity and Conservation, 13(3), 361-371.
  • Peterson, A. T., Ortega-Huerta, M. A., Bartley, J., Sánchez-Cordero, V., Soberón, J., Buddemeier, R. H., & Stockwell, D. R. (2002). Future projections for Mexican faunas under global climate change scenarios. Nature, 416(6881), 626-629.
  • R Core Team (2021). RA language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing, https://www.R-project.org/.
  • Sharp, R., Tallis, H. T., Ricketts, T., Guerry, A. D., Wood, S. A., Chaplin-Kramer, R., & Douglass, J. (2016). Invest.-Integrated Valuation of Ecosystem Services and Tradeoffs. Project, TNC; University, S.; Minnesota, U. o.
  • Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K., & Miller, H. (2007). IPCC fourth assessment report (AR4). Climate change, 374.
  • Spalding, V.M. (1890). The distribution of plants. The American Naturalist, 24(285), 819-831.
  • Thuiller, W. (2004). Patterns and uncertainties of species' range shifts under climate change. Global change biology, 10(12), 2020-2027.
  • Valavi, R., Elith, J., Lahoz‐Monfort, J. J., & Guillera‐Arroita, G. (2021). Modelling species presence‐only data with random forests. Ecography, 44(12), 1731-1742.
  • Von Humboldt, A. (1814) Essay on the geography of plants. Chicago: Foundations ofbiogeography: classic papers with commentaries. University of Chicago Press.
  • Zaniewski, A. E., Lehmann, A., & Overton, J. M. (2002). Predicting species spatial distributions using presence-only data: a case study of native New Zealand ferns. Ecological modelling, 157(2-3), 261-280.
  • Zenbilci, M., Özdemir, S., Çıvğa, A., Ünal, Y., & Oğurlu, İ. (2024). Habitat suitability modeling of wild goat (Capra aegagrus Erxleben, 1777) in different periods. Šumarski list, 148(5-6), 273-284.
There are 29 citations in total.

Details

Primary Language Turkish
Subjects Forest Biodiversity, Forest Ecosystems
Journal Section Düzce Üniversitesi Orman Fakültesi Ormancılık Dergisi 20(2)
Authors

Serkan Özdemir 0000-0002-9425-3724

Publication Date December 28, 2024
Submission Date July 28, 2024
Acceptance Date September 26, 2024
Published in Issue Year 2024 Volume: 20 Issue: 2

Cite

APA Özdemir, S. (2024). Tür Dağılım Modellemesinin Kısa Tarihi: Web of Science üzerinden Bibliyometrik Çalışma. Düzce Üniversitesi Orman Fakültesi Ormancılık Dergisi, 20(2), 334-351. https://doi.org/10.58816/duzceod.1523682

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