IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i14p8841-d866503.html
   My bibliography  Save this article

Analysis of the Sustainability of Livestock Farms in the Area of the Southwest of Bihor County to Climate Change

Author

Listed:
  • Olimpia Smaranda Mintaș

    (Department of Animal Science and Agritourism, Faculty of Environmental Protection, University of Oradea, University Street, 410087 Oradea, Romania)

  • Daniel Mierliță

    (Department of Animal Science and Agritourism, Faculty of Environmental Protection, University of Oradea, University Street, 410087 Oradea, Romania)

  • Octavian Berchez

    (Department of Agriculture-Horticulture, Faculty of Environmental Protection, University of Oradea, University Street, 410048 Oradea, Romania)

  • Alina Stanciu

    (Department of Agriculture-Horticulture, Faculty of Environmental Protection, University of Oradea, University Street, 410048 Oradea, Romania)

  • Alina Osiceanu

    (Faculty of Medicine and Pharmacy, University of Oradea, University Street, 410048 Oradea, Romania)

  • Adrian Gheorghe Osiceanu

    (Faculty of Medicine and Pharmacy, University of Oradea, University Street, 410048 Oradea, Romania)

Abstract

The concepts of sustainability and vulnerability are complementary and closely linked; mitigating the vulnerability of the human environment/climate change can increase its resilience or sustainability. Climate change can increase existing vulnerabilities and deepen socioeconomic imbalances. Measures to reduce and adapt to the effects of climate change are needed in the livestock sector, as they can help reduce the damage caused by natural disasters and other effects of climate change. The future effects of climate change are a significant challenge for livestock managers, users of livestock products and other players, as they may face a number of problems, such as the qualitative and quantitative decline in cereals (feedstock), depletion of conventional sources of energy that provide the electricity and heat needed for animal husbandry, damage to animal shelters, changes in flood frequency and the effects of flooding on the process of spreading manure on land and unforeseen operating and maintenance costs. The adaptation of the intensive animal husbandry process to climate change is a complex process considering the variability of effects, physical vulnerability, degree of socioeconomic development of the entire analyzed area, natural adaptability, health services and disaster surveillance mechanisms. The purpose of this study is to help local authorities in the process of preparing for this transition in a way that takes into account not only socioeconomic factors but also the development constraints imposed by climate change. The studied area, Ciumeghiu–Avram Iancu, located in the southern part of Bihor County, Romania, has been designated as a disadvantaged area of socioeconomic development so that economic agents can apply for the financing of rural development projects with co-financing from European funds (up to 90%). The study presents an analysis of economic development (zootechnical activities) in the southern part of Bihor County, Romania in relation to the climatic vulnerability of the area. Knowing the changes induced in an area by climate change is still a challenge for any local community, and for a socioeconomically vulnerable area, such as the study area, it is important to have at hand studies that can indicate the directions and constraints of development in dictated by these changes. Through this study, we aimed to identify a correlation between the changes induced by climate change and the development capacity of livestock farms, as many economic agents have developed or are developing technical projects for the construction of animal farms in this area. This study is based on the requirements of European reference documents, standards and guidelines. Based on the data available at this time, the applied risk analysis methodology identified a moderate risk associated with increasing extreme temperatures, changes in average precipitation, increasing average temperature, availability of water/drought resources, floods, desertification and risks associated with soil erosion, and the risk of vegetation fires. The correlation of all these factors led us to the conclusion that the area allows for the strictly controlled development of new livestock farms based on plans for the development of territorial units in the area. These units must include desertified areas and define the areas for planting vegetal curtains that will both reduce the phenomenon of erosion and block the circulation of air masses with odor released from the activity of animal husbandry and manure management. The results of the analysis show that it is necessary to take into account the diverse nature of environmental evolution/climate change in different areas of economic development specific to a development area.

Suggested Citation

  • Olimpia Smaranda Mintaș & Daniel Mierliță & Octavian Berchez & Alina Stanciu & Alina Osiceanu & Adrian Gheorghe Osiceanu, 2022. "Analysis of the Sustainability of Livestock Farms in the Area of the Southwest of Bihor County to Climate Change," Sustainability, MDPI, vol. 14(14), pages 1-32, July.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:14:p:8841-:d:866503
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/14/8841/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/14/8841/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hamed Adab & Kasturi Kanniah & Karim Solaimani, 2013. "Modeling forest fire risk in the northeast of Iran using remote sensing and GIS techniques," 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. 65(3), pages 1723-1743, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zbynek Havelka & Radim Kunes & Yevhen Kononets & Jessica Elizabeth Stokes & Lubos Smutny & Pavel Olsan & Jan Kresan & Radim Stehlik & Petr Bartos & Maohua Xiao & Pavel Kriz & Pavol Findura & David Roz, 2022. "Technology of Microclimate Regulation in Organic and Energy-Sustainable Livestock Production," Agriculture, MDPI, vol. 12(10), pages 1-24, September.

    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. Hamed Adab, 2017. "Landfire hazard assessment in the Caspian Hyrcanian forest ecoregion with the long-term MODIS active fire data," 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. 87(3), pages 1807-1825, July.
    2. Dingli Liu & Zhisheng Xu & Chuangang Fan, 2019. "Predictive analysis of fire frequency based on daily temperatures," 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. 97(3), pages 1175-1189, July.
    3. Shruti Sachdeva & Tarunpreet Bhatia & A. K. Verma, 2018. "GIS-based evolutionary optimized Gradient Boosted Decision Trees for forest fire susceptibility mapping," 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. 92(3), pages 1399-1418, July.
    4. José Manuel Zúñiga-Vásquez & Marín Pompa-García, 2019. "The occurrence of forest fires in Mexico presents an altitudinal tendency: a geospatial analysis," 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. 96(1), pages 213-224, March.
    5. Hamed Adab & Kasturi Devi Kanniah & Karim Solaimani, 2021. "Remote sensing-based operational modeling of fuel ignitability in Hyrcanian mixed forest, Iran," 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. 108(1), pages 253-283, August.
    6. Gianluigi Busico & Elisabetta Giuditta & Nerantzis Kazakis & Nicolò Colombani, 2019. "A Hybrid GIS and AHP Approach for Modelling Actual and Future Forest Fire Risk Under Climate Change Accounting Water Resources Attenuation Role," Sustainability, MDPI, vol. 11(24), pages 1-20, December.
    7. Saeedeh Eskandari & Mahdis Amiri & Nitheshnirmal Sãdhasivam & Hamid Reza Pourghasemi, 2020. "Comparison of new individual and hybrid machine learning algorithms for modeling and mapping fire hazard: a supplementary analysis of fire hazard in different counties of Golestan Province in Iran," 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. 104(1), pages 305-327, October.
    8. Roghayeh Jahdi & Michele Salis & Fermin J. Alcasena & Mahdi Arabi & Bachisio Arca & Pierpaolo Duce, 2020. "Evaluating landscape-scale wildfire exposure in northwestern Iran," 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. 101(3), pages 911-932, April.
    9. Abolfazl Jaafari & Omid Rahmati & Eric K. Zenner & Davood Mafi-Gholami, 2022. "Anthropogenic activities amplify wildfire occurrence in the Zagros eco-region of western Iran," 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. 114(1), pages 457-473, October.
    10. Anuj Tiwari & Mohammad Shoab & Abhilasha Dixit, 2021. "GIS-based forest fire susceptibility modeling in Pauri Garhwal, India: a comparative assessment of frequency ratio, analytic hierarchy process and fuzzy modeling techniques," 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. 105(2), pages 1189-1230, January.
    11. Osama Ashraf Mohammed & Sasan Vafaei & Mehdi Mirzaei Kurdalivand & Sabri Rasooli & Chaolong Yao & Tongxin Hu, 2022. "A Comparative Study of Forest Fire Mapping Using GIS-Based Data Mining Approaches in Western Iran," Sustainability, MDPI, vol. 14(20), pages 1-13, October.
    12. Ghafar Salavati & Ebrahim Saniei & Ebrahim Ghaderpour & Quazi K. Hassan, 2022. "Wildfire Risk Forecasting Using Weights of Evidence and Statistical Index Models," Sustainability, MDPI, vol. 14(7), pages 1-15, March.
    13. Ali Akbar JAFARZADEH & Ali MAHDAVI & Heydar JAFARZADEH, 2017. "Evaluation of forest fire risk using the Apriori algorithm and fuzzy c-means clustering," Journal of Forest Science, Czech Academy of Agricultural Sciences, vol. 63(8), pages 370-380.
    14. Reshma T. Vilasan & Vijay S. Kapse, 2022. "Evaluation of the prediction capability of AHP and F-AHP methods in flood susceptibility mapping of Ernakulam district (India)," 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. 112(2), pages 1767-1793, June.
    15. Faisal, Abdullah Al & Kafy, Abdulla - Al & Afroz, Farzana & Rahaman, Zullyadini A., 2023. "Exploring and forecasting spatial and temporal patterns of fire hazard risk in Nepal's tiger conservation zones," Ecological Modelling, Elsevier, vol. 476(C).
    16. André Padrão & Lia Duarte & Ana Cláudia Teodoro, 2022. "A GIS Plugin for Susceptibility Modeling: Case Study of Wildfires in Vila Nova de Foz Côa," Land, MDPI, vol. 11(7), pages 1-21, July.
    17. Naderpour, Mohsen & Rizeei, Hossein Mojaddadi & Khakzad, Nima & Pradhan, Biswajeet, 2019. "Forest fire induced Natech risk assessment: A survey of geospatial technologies," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    18. Sarkawt G. Salar & Arsalan Ahmed Othman & Sabri Rasooli & Salahalddin S. Ali & Zaid T. Al-Attar & Veraldo Liesenberg, 2022. "GIS-Based Modeling for Vegetated Land Fire Prediction in Qaradagh Area, Kurdistan Region, Iraq," Sustainability, MDPI, vol. 14(10), pages 1-31, May.

    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:14:y:2022:i:14:p:8841-:d:866503. 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.