IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v486y2023ics0304380023002442.html
   My bibliography  Save this article

Species distribution modelling in the Southwestern Atlantic Ocean: A systematic review and trends

Author

Listed:
  • Rodrigues, Lucas dos Santos
  • Daudt, Nicholas Winterle
  • Cardoso, Luis Gustavo
  • Kinas, Paul Gerhard
  • Conesa, David
  • Pennino, Maria Grazia

Abstract

Species distribution modelling (SDM) of marine organisms is widely developed for biogeography, ecology and management purposes. However, most studies continue to focus on the Global North, with fewer examples for the Global South. We carried out a bibliometric analysis to characterise aspects of studies conducting SDM for species in the Southwestern Atlantic Ocean (SWAO), focusing on the type of input data, taxonomic groups studied, focus of research, methods applied, and international collaboration between countries. Studies on megafauna and fisheries resources, based on presence-only and scenopoetic input data, applying Maximum Entropy (MaxEnt) and generalized linear/additive models (GLM/GAM) predominate. Models applied to biogeography/current species distribution were the most common, followed by biological invasion. Brazil figures as the most prolific country publishing in SWAO, and has more collaborations with the United States of America, Europe, and South Africa than with its neighbours Uruguay and Argentina, who formed a separate cluster. Research groups based on coauthorship of the 30 most frequent authors seem to be mostly isolated, with only two research groups collaborating to each other. In addition, we fit a Binomial generalised linear model (BGLM) to explore how many predictors (layers) would be sufficient to reach an excellent modelling performance based on Area Under the Curve (AUC) values. The BGLM indicated at least 5–8 layers would be necessary to have a 50 % chance of achieving excellent model performance (AUC ≥ 0.9), but we urge caution regarding this result and briefly discuss it. The literature review was used as a baseline to discuss aspects of our findings and highlight the need to increase SDM application in the SWAO and to strengthen international collaboration between Latin American countries. Finally, we provide recommendations on how researchers could approach some of the gaps we found.

Suggested Citation

  • Rodrigues, Lucas dos Santos & Daudt, Nicholas Winterle & Cardoso, Luis Gustavo & Kinas, Paul Gerhard & Conesa, David & Pennino, Maria Grazia, 2023. "Species distribution modelling in the Southwestern Atlantic Ocean: A systematic review and trends," Ecological Modelling, Elsevier, vol. 486(C).
    • Handle: RePEc:eee:ecomod:v:486:y:2023:i:c:s0304380023002442
    DOI: 10.1016/j.ecolmodel.2023.110514
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380023002442
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ecolmodel.2023.110514?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Donthu, Naveen & Kumar, Satish & Mukherjee, Debmalya & Pandey, Nitesh & Lim, Weng Marc, 2021. "How to conduct a bibliometric analysis: An overview and guidelines," Journal of Business Research, Elsevier, vol. 133(C), pages 285-296.
    2. Aria, Massimo & Cuccurullo, Corrado, 2017. "bibliometrix: An R-tool for comprehensive science mapping analysis," Journal of Informetrics, Elsevier, vol. 11(4), pages 959-975.
    3. Bradley A Pickens & Rachel Carroll & Michael J Schirripa & Francesca Forrestal & Kevin D Friedland & J Christopher Taylor, 2021. "A systematic review of spatial habitat associations and modeling of marine fish distribution: A guide to predictors, methods, and knowledge gaps," PLOS ONE, Public Library of Science, vol. 16(5), pages 1-21, May.
    4. Ready, Jonathan & Kaschner, Kristin & South, Andy B. & Eastwood, Paul D. & Rees, Tony & Rius, Josephine & Agbayani, Eli & Kullander, Sven & Froese, Rainer, 2010. "Predicting the distributions of marine organisms at the global scale," Ecological Modelling, Elsevier, vol. 221(3), pages 467-478.
    5. Melo-Merino, Sara M. & Reyes-Bonilla, Héctor & Lira-Noriega, Andrés, 2020. "Ecological niche models and species distribution models in marine environments: A literature review and spatial analysis of evidence," Ecological Modelling, Elsevier, vol. 415(C).
    6. Barbosa, Fabiana G. & Schneck, Fabiana, 2015. "Characteristics of the top-cited papers in species distribution predictive models," Ecological Modelling, Elsevier, vol. 313(C), pages 77-83.
    7. Sillero, Neftalí & Campos, João Carlos & Arenas-Castro, Salvador & Barbosa, A.Márcia, 2023. "A curated list of R packages for ecological niche modelling," Ecological Modelling, Elsevier, vol. 476(C).
    8. Sillero, Neftalí, 2011. "What does ecological modelling model? A proposed classification of ecological niche models based on their underlying methods," Ecological Modelling, Elsevier, vol. 222(8), pages 1343-1346.
    9. Derek P. Tittensor & Camilo Mora & Walter Jetz & Heike K. Lotze & Daniel Ricard & Edward Vanden Berghe & Boris Worm, 2010. "Global patterns and predictors of marine biodiversity across taxa," Nature, Nature, vol. 466(7310), pages 1098-1101, August.
    10. Xavier Barber & David Conesa & Antonio López-Quílez & Joaquín Martínez-Minaya & Iosu Paradinas & Maria Grazia Pennino, 2021. "Incorporating Biotic Information in Species Distribution Models: A Coregionalized Approach," Mathematics, MDPI, vol. 9(4), pages 1-12, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Quan-Hoang Vuong & Huyen Thanh T. Nguyen & Thanh-Hang Pham & Manh-Toan Ho & Minh-Hoang Nguyen, 2021. "Assessing the ideological homogeneity in entrepreneurial finance research by highly cited publications," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-11, December.
    2. Shuangqing Sheng & Wei Song & Hua Lian & Lei Ning, 2022. "Review of Urban Land Management Based on Bibliometrics," Land, MDPI, vol. 11(11), pages 1-25, November.
    3. Gour Gobinda Goswami & Tahmid Labib, 2022. "Modeling COVID-19 Transmission Dynamics: A Bibliometric Review," IJERPH, MDPI, vol. 19(21), pages 1-19, October.
    4. Das, Kallol & Patel, Jayesh D. & Sharma, Anuj & Shukla, Yupal, 2023. "Creativity in marketing: Examining the intellectual structure using scientometric analysis and topic modeling," Journal of Business Research, Elsevier, vol. 154(C).
    5. Ying Liang & Wei Song, 2022. "Ecological and Environmental Effects of Land Use and Cover Changes on the Qinghai-Tibetan Plateau: A Bibliometric Review," Land, MDPI, vol. 11(12), pages 1-23, November.
    6. Lanzalonga Federico & Chmet Federico & Petrolo Basilio & Brescia Valerio, 2023. "Exploring Diversity Management to Avoid Social Washing and Pinkwashing: Using Bibliometric Analysis to Shape Future Research Directions," Journal of Intercultural Management, Sciendo, vol. 15(1), pages 41-65, March.
    7. Jin Su & Mo Wang & Mohd Adib Mohammad Razi & Norlida Mohd Dom & Noralfishah Sulaiman & Lai-Wai Tan, 2023. "A Bibliometric Review of Nature-Based Solutions on Urban Stormwater Management," Sustainability, MDPI, vol. 15(9), pages 1-23, April.
    8. Manta Eduard Mihai & Davidescu Adriana Ana Maria & Geambasu Maria Cristina & Florescu Margareta Stela, 2023. "Exploring the research area of direct taxation. An empirical analysis based on bibliometric analysis results," Management & Marketing, Sciendo, vol. 18(s1), pages 355-383, December.
    9. Khan, Ashraf & Goodell, John W. & Hassan, M. Kabir & Paltrinieri, Andrea, 2022. "A bibliometric review of finance bibliometric papers," Finance Research Letters, Elsevier, vol. 47(PA).
    10. Ajjima Jiravichai & Ruth Banomyong, 2022. "A Proposed Methodology for Literature Review on Operational Risk Management in Banks," Risks, MDPI, vol. 10(5), pages 1-18, May.
    11. Deepa Sharma & Suman Chakraborty & Ashwath Ananda Rao & Lumen Shawn Lobo, 2023. "The Relationship of Corporate Social Responsibility and Firm Performance: A Bibliometric Overview," SAGE Open, , vol. 13(1), pages 21582440231, March.
    12. Riaz Tabassum & Selama Aslam Izah & Nor Normaziah Mohd & Hassan Ahmad Fahmi Sheikh, 2024. "Meaningful Review of Existing Trends, Expansion, and Future Directions of Green Bond Research: A Bibliometric Approach," Studia Universitatis „Vasile Goldis” Arad – Economics Series, Sciendo, vol. 34(1), pages 1-36, March.
    13. Albiona Pestisha & Zoltán Gabnai & Aidana Chalgynbayeva & Péter Lengyel & Attila Bai, 2023. "On-Farm Renewable Energy Systems: A Systematic Review," Energies, MDPI, vol. 16(2), pages 1-25, January.
    14. Zamani, Mehdi & Yalcin, Haydar & Naeini, Ali Bonyadi & Zeba, Gordana & Daim, Tugrul U, 2022. "Developing metrics for emerging technologies: identification and assessment," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    15. Abidin Kemeç & Ayşenur Tarakcıoglu Altınay, 2023. "Sustainable Energy Research Trend: A Bibliometric Analysis Using VOSviewer, RStudio Bibliometrix, and CiteSpace Software Tools," Sustainability, MDPI, vol. 15(4), pages 1-21, February.
    16. Satish Kumar & Riya Sureka & Weng Marc Lim & Sachin Kumar Mangla & Nisha Goyal, 2021. "What do we know about business strategy and environmental research? Insights from Business Strategy and the Environment," Business Strategy and the Environment, Wiley Blackwell, vol. 30(8), pages 3454-3469, December.
    17. Pereira, Vijay & Bamel, Umesh & Paul, Happy & Varma, Arup, 2022. "Personality and safety behavior: An analysis of worldwide research on road and traffic safety leading to organizational and policy implications," Journal of Business Research, Elsevier, vol. 151(C), pages 185-196.
    18. Mohammed H. Alzard & Hilal El-Hassan & Tamer El-Maaddawy & Marwa Alsalami & Fatma Abdulrahman & Ashraf Aly Hassan, 2022. "A Bibliometric Analysis of the Studies on Self-Healing Concrete Published between 1974 and 2021," Sustainability, MDPI, vol. 14(18), pages 1-22, September.
    19. Mbarki, Imen & Khan, Muhammad Arif & Karim, Sitara & Paltrinieri, Andrea & Lucey, Brian M., 2023. "Unveiling commodities-financial markets intersections from a bibliometric perspective," Resources Policy, Elsevier, vol. 83(C).
    20. Simbarashe Jombo & Mohamed A. M. Abd Elbasit & Anesu D. Gumbo & Nthaduleni S. Nethengwe, 2023. "Remote Sensing Application in Mountainous Environments: A Bibliographic Analysis," IJERPH, MDPI, vol. 20(4), pages 1-17, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecomod:v:486:y:2023:i:c:s0304380023002442. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/ecological-modelling .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.