IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v12y2023i10p1914-d1258528.html
   My bibliography  Save this article

Climate Change Impacts on Grassland Vigour in Northern Portugal

Author

Listed:
  • Oiliam Stolarski

    (Centre for the Research and Technology of Agri-Environmental and Biological Sciences (CITAB), Institute for Innovation, Capacity Building and Sustainability of Agri-Food Production (Inov4Agro), Universidade de Trás-os-Montes e Alto Douro (UTAD), 5000-801 Vila Real, Portugal)

  • João A. Santos

    (Centre for the Research and Technology of Agri-Environmental and Biological Sciences (CITAB), Institute for Innovation, Capacity Building and Sustainability of Agri-Food Production (Inov4Agro), Universidade de Trás-os-Montes e Alto Douro (UTAD), 5000-801 Vila Real, Portugal)

  • André Fonseca

    (Centre for the Research and Technology of Agri-Environmental and Biological Sciences (CITAB), Institute for Innovation, Capacity Building and Sustainability of Agri-Food Production (Inov4Agro), Universidade de Trás-os-Montes e Alto Douro (UTAD), 5000-801 Vila Real, Portugal)

  • Chenyao Yang

    (Centre for the Research and Technology of Agri-Environmental and Biological Sciences (CITAB), Institute for Innovation, Capacity Building and Sustainability of Agri-Food Production (Inov4Agro), Universidade de Trás-os-Montes e Alto Douro (UTAD), 5000-801 Vila Real, Portugal)

  • Henrique Trindade

    (Centre for the Research and Technology of Agri-Environmental and Biological Sciences (CITAB), Institute for Innovation, Capacity Building and Sustainability of Agri-Food Production (Inov4Agro), Universidade de Trás-os-Montes e Alto Douro (UTAD), 5000-801 Vila Real, Portugal)

  • Helder Fraga

    (Centre for the Research and Technology of Agri-Environmental and Biological Sciences (CITAB), Institute for Innovation, Capacity Building and Sustainability of Agri-Food Production (Inov4Agro), Universidade de Trás-os-Montes e Alto Douro (UTAD), 5000-801 Vila Real, Portugal)

Abstract

Grasslands are key elements of the global agricultural system, covering around two-thirds of all agricultural areas and playing an important role in biodiversity conservation, food security, and balancing the carbon cycle. Climate change is a growing challenge for the agricultural sector and may threaten grasslands. To address these challenges, it is vital to conduct in-depth climate studies to understand the vulnerability of grasslands. In this study, machine learning was used to build an advanced model able to evaluate the future impact of climate change on grassland vigour. The objective was to identify the most vulnerable grassland areas, analyse the interaction between climate and grassland performance, and outline management strategies against the detrimental implications of climate change. A Random Forest (RF) regression was used to model the Normalised Difference Vegetation Index (NDVI) using the Standardised Precipitation-Evapotranspiration Index (SPEI). The model explained 76% of the NDVI variability. The foremost significant predictors of grassland vigour are the SPEI with temporal lags of 1, 4, and 12 months. These findings suggest that the vegetative status of grasslands exhibits high sensitivity to short-term drought while also being influenced by the memory of past climatic events over longer periods. Future projections indicate an overall reduction in grassland vigour, mostly in RCP8.5. The results indicate that negative effects will be more pronounced in mountainous regions, which currently host the most vigorous grasslands. Dry lowlands in the north should continue to have the lowest vigour in the future. A substantial reduction in vigour is expected in autumn, with an effect on grassland phenology. The development of grasslands in winter, favoured by increasing temperatures and precipitation, can advance the harvesting of grassland (cutting) and the grazing of livestock. To ensure that vigour is maintained in less favourable zones, adaptation measures will be needed, as well as more efficient management of highlands to provide an adequate level of production.

Suggested Citation

  • Oiliam Stolarski & João A. Santos & André Fonseca & Chenyao Yang & Henrique Trindade & Helder Fraga, 2023. "Climate Change Impacts on Grassland Vigour in Northern Portugal," Land, MDPI, vol. 12(10), pages 1-18, October.
    • Handle: RePEc:gam:jlands:v:12:y:2023:i:10:p:1914-:d:1258528
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/12/10/1914/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/12/10/1914/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. W. A. Obermeier & L. W. Lehnert & C. I. Kammann & C. Müller & L. Grünhage & J. Luterbacher & M. Erbs & G. Moser & R. Seibert & N. Yuan & J. Bendix, 2017. "Reduced CO2 fertilization effect in temperate C3 grasslands under more extreme weather conditions," Nature Climate Change, Nature, vol. 7(2), pages 137-141, February.
    2. Nana Luo & Dehua Mao & Bolong Wen & Xingtu Liu, 2020. "Climate Change Affected Vegetation Dynamics in the Northern Xinjiang of China: Evaluation by SPEI and NDVI," Land, MDPI, vol. 9(3), pages 1-18, March.
    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. Xiaoyan Tang & Yongjiu Feng & Chen Gao & Zhenkun Lei & Shurui Chen & Rong Wang & Yanmin Jin & Xiaohua Tong, 2023. "Entropy-weight-based spatiotemporal drought assessment using MODIS products and Sentinel-1A images in Urumqi, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 119(1), pages 387-408, October.
    2. Zefeng Chen & Weiguang Wang & Giovanni Forzieri & Alessandro Cescatti, 2024. "Transition from positive to negative indirect CO2 effects on the vegetation carbon uptake," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    3. Chunbo Chen & Chi Zhang, 2017. "Projecting the CO 2 and Climatic Change Effects on the Net Primary Productivity of the Urban Ecosystems in Phoenix, AZ in the 21st Century under Multiple RCP (Representative Concentration Pathway) Sce," Sustainability, MDPI, vol. 9(8), pages 1-20, August.
    4. Yang Wang & Remina Shataer & Tingting Xia & Xueer Chang & Hui Zhen & Zhi Li, 2021. "Evaluation on the Change Characteristics of Ecosystem Service Function in the Northern Xinjiang Based on Land Use Change," Sustainability, MDPI, vol. 13(17), pages 1-17, August.
    5. Xiuhua Cai & Wenqian Zhang & Cunjie Zhang & Qiang Zhang & Jingli Sun & Chen Cheng & Wenjie Fan & Ying Yu & Xiaoling Liu, 2022. "Identification and Spatial-Temporal Variation Characteristics of Regional Drought Processes in China," Land, MDPI, vol. 11(6), pages 1-21, June.
    6. Yongchao Duan & Min Luo & Xiufeng Guo & Peng Cai & Fu Li, 2021. "Study on the Relationship between Snowmelt Runoff for Different Latitudes and Vegetation Growth Based on an Improved SWAT Model in Xinjiang, China," Sustainability, MDPI, vol. 13(3), pages 1-26, January.
    7. Xiuhua Cai & Wenqian Zhang & Xiaoyi Fang & Qiang Zhang & Cunjie Zhang & Dong Chen & Chen Cheng & Wenjie Fan & Ying Yu, 2021. "Identification of Regional Drought Processes in North China Using MCI Analysis," Land, MDPI, vol. 10(12), pages 1-19, December.
    8. Marc C. Heuermann & Dominic Knoch & Astrid Junker & Thomas Altmann, 2023. "Natural plant growth and development achieved in the IPK PhenoSphere by dynamic environment simulation," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    9. Shengxin Lan & Zuoji Dong, 2022. "Incorporating Vegetation Type Transformation with NDVI Time-Series to Study the Vegetation Dynamics in Xinjiang," Sustainability, MDPI, vol. 14(1), pages 1-15, January.
    10. Haochen Yu & Zhengfu Bian & Shouguo Mu & Junfang Yuan & Fu Chen, 2020. "Effects of Climate Change on Land Cover Change and Vegetation Dynamics in Xinjiang, China," IJERPH, MDPI, vol. 17(13), pages 1-25, July.
    11. Huaijun Wang & Zhi Li & Lei Cao & Ru Feng & Yingping Pan, 2021. "Response of NDVI of Natural Vegetation to Climate Changes and Drought in China," Land, MDPI, vol. 10(9), pages 1-24, September.
    12. Yu Zhang & Na Gong & Huade Zhu, 2023. "Vegetation Dynamics and Food Security against the Background of Ecological Restoration in Hubei Province, China," IJERPH, MDPI, vol. 20(2), pages 1-18, January.
    13. Wan-Jiun Chen, 2022. "Toward Sustainability: Dynamics of Total Carbon Dioxide Emissions, Aggregate Income, Non-Renewable Energy, and Renewable Power," Sustainability, MDPI, vol. 14(5), pages 1-27, February.
    14. Shuping Fan & Peng Li & Qi He & Jiaru Cheng & Mingfeng Zhang & Nan Wu & Song Yang & Shidong Pan, 2022. "Study on the Spatial-Temporal Evolution of Land Use Ecosystem Service Value and Its Zoning Management and Control in the Typical Alpine Valley Area of Southeast Tibet—Empirical Analysis Based on Panel," Sustainability, MDPI, vol. 14(16), pages 1-19, August.
    15. Ignacio Perez Dominguez & Thomas Fellmann, 2018. "PESETA III: Agro-economic analysis of climate change impacts in Europe," JRC Research Reports JRC113743, Joint Research Centre.
    16. Xiuwei Xing & Jing Qian & Xi Chen & Chaoliang Chen & Jiayu Sun & Shujie Wei & Duman Yimamaidi & Zhahan Zhanar, 2022. "Analysis of Effects of Recent Changes in Hydrothermal Conditions on Vegetation in Central Asia," Land, MDPI, vol. 11(3), pages 1-27, February.
    17. Yan Li & Jie Gong & Yunxia Zhang & Bingli Gao, 2022. "NDVI-Based Greening of Alpine Steppe and Its Relationships with Climatic Change and Grazing Intensity in the Southwestern Tibetan Plateau," Land, MDPI, vol. 11(7), pages 1-16, June.

    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:jlands:v:12:y:2023:i:10:p:1914-:d:1258528. 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.