IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i8p3458-d1379704.html
   My bibliography  Save this article

Climate Change Impact on the Distribution of Forest Species in the Brazilian Amazon

Author

Listed:
  • Ingrid Lana Lima de Morais

    (Faculty of Agricultural Sciences, Federal University of Amazonas, Avenue Rodrigo Otávio, 3000, Manaus 69060-000, AM, Brazil)

  • Alexandra Amaro de Lima

    (Institute of Technology and Education Galileo of Amazon, Avenue Joaquim Nabuco, 1950, Manaus 69020-030, AM, Brazil)

  • Ivinne Nara Lobato dos Santos

    (Faculty of Agricultural Sciences, Federal University of Amazonas, Avenue Rodrigo Otávio, 3000, Manaus 69060-000, AM, Brazil)

  • Carlos Meneses

    (Graduate Program in Agricultural Sciences, Department of Biology, Center for Biological and Health Sciences, State University of Paraíba, Campina Grande 58429-500, PB, Brazil)

  • Rogério Freire da Silva

    (Graduate Program in Agricultural Sciences, Department of Biology, Center for Biological and Health Sciences, State University of Paraíba, Campina Grande 58429-500, PB, Brazil)

  • Ricardo Lopes

    (Embrapa Western Amazon, Route AM 10, Km 29, s/n, C.P. 319, Manaus 69010-970, AM, Brazil)

  • Santiago Linorio Ferreyra Ramos

    (Institute of Exact Sciences and Technology, Federal University of Amazonas, Nossa Senhora do Rosário, 3863, Itacoatiara 69103-128, AM, Brazil)

  • Ananda Virginia de Aguiar

    (Pollen Laboratory, Embrapa Florestas, Km 111, BR 476, CP. 319, Colombo 83411-000, PR, Brazil)

  • Marcos Silveira Wrege

    (Pollen Laboratory, Embrapa Florestas, Km 111, BR 476, CP. 319, Colombo 83411-000, PR, Brazil)

  • Maria Teresa Gomes Lopes

    (Faculty of Agricultural Sciences, Federal University of Amazonas, Avenue Rodrigo Otávio, 3000, Manaus 69060-000, AM, Brazil)

Abstract

Studies using ecological niche models highlight the vulnerability of forest species to climate change. This work aimed to analyze the distribution of timber species Aspidosperma desmanthum , Cariniana micranta , Clarisia racemosa , Couratari oblongifolia , and Vouchysia guianensis , which are targets of deforestation, to predict the impacts of climate change and identify areas for their conservation in the Amazon. For this purpose, 37 environmental variables were used, including climatic and edaphic factors. The models were fitted using five algorithms, and their performance was evaluated by the metrics Area Under the Curve (AUC), True Skill Statistic, and Sorensen Index. The deforestation analysis was conducted using data accumulated over a period of 14 years. The study indicated that under the most pessimistic predictions, considering continued high emissions of greenhouse gases (GHGs) from the use of fossil fuels, SSP5–8.5, potential habitat loss for the studied species was more significant. Analyses of the species show that the Western Amazon has a greater climatic suitability area for the conservation of its genetic resources. Further study of the accumulated deforestation over 14 years showed a reduction in area for all species. Therefore, in situ conservation policies and deforestation reduction are recommended for the perpetuation of the analyzed forest species.

Suggested Citation

  • Ingrid Lana Lima de Morais & Alexandra Amaro de Lima & Ivinne Nara Lobato dos Santos & Carlos Meneses & Rogério Freire da Silva & Ricardo Lopes & Santiago Linorio Ferreyra Ramos & Ananda Virginia de A, 2024. "Climate Change Impact on the Distribution of Forest Species in the Brazilian Amazon," Sustainability, MDPI, vol. 16(8), pages 1-15, April.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:8:p:3458-:d:1379704
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/8/3458/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/16/8/3458/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Boria, Robert A. & Olson, Link E. & Goodman, Steven M. & Anderson, Robert P., 2014. "Spatial filtering to reduce sampling bias can improve the performance of ecological niche models," Ecological Modelling, Elsevier, vol. 275(C), pages 73-77.
    2. Santiago José Elías Velazco & Franklin Galvão & Fabricio Villalobos & Paulo De Marco Júnior, 2017. "Using worldwide edaphic data to model plant species niches: An assessment at a continental extent," PLOS ONE, Public Library of Science, vol. 12(10), pages 1-24, October.
    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. B Eugene Smith & Mark K Johnston & Robert Lücking, 2016. "From GenBank to GBIF: Phylogeny-Based Predictive Niche Modeling Tests Accuracy of Taxonomic Identifications in Large Occurrence Data Repositories," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-15, March.
    2. Ramos, Rodrigo Soares & Kumar, Lalit & Shabani, Farzin & Picanço, Marcelo Coutinho, 2019. "Risk of spread of tomato yellow leaf curl virus (TYLCV) in tomato crops under various climate change scenarios," Agricultural Systems, Elsevier, vol. 173(C), pages 524-535.
    3. Fourcade, Yoan, 2021. "Fine-tuning niche models matters in invasion ecology. A lesson from the land planarian Obama nungara," Ecological Modelling, Elsevier, vol. 457(C).
    4. Feng Dong & Chih-Ming Hung & Shou-Hsien Li & Xiao-Jun Yang, 2021. "Potential Himalayan community turnover through the Late Pleistocene," Climatic Change, Springer, vol. 164(1), pages 1-10, January.
    5. Christophe Botella & Alexis Joly & Pascal Monestiez & Pierre Bonnet & François Munoz, 2020. "Bias in presence-only niche models related to sampling effort and species niches: Lessons for background point selection," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-18, May.
    6. Dana H. Mills & Michael L. McKinney, 2024. "Climate Change and Jump Dispersal Drive Invasion of the Rosy Wolfsnail ( Euglandina rosea ) in the United States," Sustainability, MDPI, vol. 16(5), pages 1-14, February.
    7. Zeng, Yiwen & Low, Bi Wei & Yeo, Darren C.J., 2016. "Novel methods to select environmental variables in MaxEnt: A case study using invasive crayfish," Ecological Modelling, Elsevier, vol. 341(C), pages 5-13.
    8. Schartel, Tyler E. & Cao, Yong, 2024. "Background selection complexity influences Maxent predictive performance in freshwater systems," Ecological Modelling, Elsevier, vol. 488(C).
    9. Van Eupen, Camille & Maes, Dirk & Herremans, Marc & Swinnen, Kristijn R.R. & Somers, Ben & Luca, Stijn, 2021. "The impact of data quality filtering of opportunistic citizen science data on species distribution model performance," Ecological Modelling, Elsevier, vol. 444(C).
    10. Yinglian Qi & Xiaoyan Pu & Yaxiong Li & Dingai Li & Mingrui Huang & Xuan Zheng & Jiaxin Guo & Zhi Chen, 2022. "Prediction of Suitable Distribution Area of Plateau pika ( Ochotona curzoniae ) in the Qinghai–Tibet Plateau under Shared Socioeconomic Pathways (SSPs)," Sustainability, MDPI, vol. 14(19), pages 1-23, September.
    11. Sillero, Neftalí & Arenas-Castro, Salvador & Enriquez‐Urzelai, Urtzi & Vale, Cândida Gomes & Sousa-Guedes, Diana & Martínez-Freiría, Fernando & Real, Raimundo & Barbosa, A.Márcia, 2021. "Want to model a species niche? A step-by-step guideline on correlative ecological niche modelling," Ecological Modelling, Elsevier, vol. 456(C).
    12. Carlos Yañez-Arenas & A. Townsend Peterson & Karla Rodríguez-Medina & Narayani Barve, 2016. "Mapping current and future potential snakebite risk in the new world," Climatic Change, Springer, vol. 134(4), pages 697-711, February.
    13. Carlos Yañez-Arenas & A. Townsend Peterson & Karla Rodríguez-Medina & Narayani Barve, 2016. "Mapping current and future potential snakebite risk in the new world," Climatic Change, Springer, vol. 134(4), pages 697-711, February.
    14. John M. Humphreys & Robert B. Srygley & David H. Branson, 2022. "Geographic Variation in Migratory Grasshopper Recruitment under Projected Climate Change," Geographies, MDPI, vol. 2(1), pages 1-19, January.
    15. Herkt, K. Matthias B. & Barnikel, Günter & Skidmore, Andrew K. & Fahr, Jakob, 2016. "A high-resolution model of bat diversity and endemism for continental Africa," Ecological Modelling, Elsevier, vol. 320(C), pages 9-28.
    16. Marsh, Charles J. & Gavish, Yoni & Kuemmerlen, Mathias & Stoll, Stefan & Haase, Peter & Kunin, William E., 2023. "SDM profiling: A tool for assessing the information-content of sampled and unsampled locations for species distribution models," Ecological Modelling, Elsevier, vol. 475(C).
    17. Dimitra-Lida Rammou & Christos Astaras & Despina Migli & George Boutsis & Antonia Galanaki & Theodoros Kominos & Dionisios Youlatos, 2022. "European Ground Squirrels at the Edge: Current Distribution Status and Anticipated Impact of Climate on Europe’s Southernmost Population," Land, MDPI, vol. 11(2), pages 1-18, February.
    18. Sutton, G.F. & Martin, G.D., 2022. "Testing MaxEnt model performance in a novel geographic region using an intentionally introduced insect," Ecological Modelling, Elsevier, vol. 473(C).
    19. Pimenta, Mayra & Andrade, André Felipe Alves de & Fernandes, Fernando Hiago Souza & Amboni, Mayra Pereira de Melo & Almeida, Renata Silva & Soares, Ana Hermínia Simões de Bello & Falcon, Guth Berger &, 2022. "One size does not fit all: Priority areas for real world problems," Ecological Modelling, Elsevier, vol. 470(C).
    20. Fernandez, Marc & Sillero, Neftali & Yesson, Chris, 2022. "To be or not to be: the role of absences in niche modelling for highly mobile species in dynamic marine environments," Ecological Modelling, Elsevier, vol. 471(C).

    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:gam:jsusta:v:16:y:2024:i:8:p:3458-:d:1379704. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.