Statistical Relationships Between Agricultural Indicators and Annual Average Air Temperature in Mongolia
Keywords:
annual average air temperature, agricultural indicators, correlation analysis, Laplace function, linear regression, Mongolia: spatial representationAbstract
This study investigates the statistical relationships between agricultural indicators and annual average air temperature in Mongolia using long-term datasets covering the period 1975–2024. The analysis integrates linear algebra, mathematical statistics, probability distribution theory, correlation analysis, linear regression analysis, and Laplace-function-based spatial representation to evaluate associations between agricultural activities and temperature variability across representative agro-ecological regions of Mongolia. Five provinces representing the major agricultural zones were selected as sample regions. Distribution analysis confirmed the suitability of the datasets for subsequent statistical modeling. Correlation analysis revealed that livestock-related indicators generally exhibited stronger associations with annual average air temperature than crop-production indicators. Among livestock categories, goats, small livestock populations, and total livestock numbers showed the highest correlation coefficients and the broadest spatial representation within strong-correlation classes. Regression analysis further identified horse populations, goat populations, and vegetable production as indicators exhibiting relatively strong positive statistical relationships with annual average air temperature. The Laplace-function analysis enabled the spatial extrapolation of correlation and regression classes across representative agricultural regions, providing a probabilistic interpretation of the observed relationships. The results suggest that livestock dynamics are more closely associated with long-term temperature variability than crop-production activities in Mongolia. The proposed methodological framework provides a useful approach for investigating agricultural–climate interactions and may support future environmental assessment and sustainable agricultural policy development.
0
References
[1]. IPCC, Climate Change 2023: Synthesis Report. Geneva, Switzerland: Intergovernmental Panel on Climate Change, 2023. Available: https://www.ipcc.ch/report/ar6/syr/
[2]. P. R. Shukla et al., Climate Change and Land: An IPCC Special Report on Climate Change, Desertification, Land Degradation, Sustainable Land Management, Food Security and Greenhouse Gas Fluxes in Terrestrial Ecosystems. Geneva, Switzerland: IPCC, 2019. Available: https://www.ipcc.ch/srccl/
[3]. P. Smith et al., "Agriculture, Forestry and Other Land Use (AFOLU)," in Climate Change 2014: Mitigation of Climate Change. Cambridge, U.K.: Cambridge University Press, 2014, pp. 811-922. https://doi.org/10.1017/CBO9781107415416.017
[4]. F. N. Tubiello et al., "Greenhouse gas emissions from food systems: Building the evidence base," Environmental Research Letters, vol. 16, no. 6, Art. no. 065007, 2021. https://doi.org/10.1088/1748-9326/ac018e
[5]. F. N. Tubiello et al., "Pre- and post-production processes increasingly dominate greenhouse gas emissions from agri-food systems," Earth System Science Data, vol. 14, pp. 1795-1809, 2022. https://doi.org/10.5194/essd-14-1795-2022
[6]. T. Sternberg, "Climate hazards in Mongolia: Livestock, rangelands and unmanaged risk," Natural Hazards, vol. 63, no. 1, pp. 59-72, 2012. DOI: https://doi.org/10.1007/s11069-012-0104-z
[7]. National Statistics Office of Mongolia, Agricultural Sector Statistics 2024. Ulaanbaatar, Mongolia: NSO, 2024. Available: https://www.1212.mn
[8]. P. Batima, L. Natsagdorj, P. Gombluudev, and B. Erdenetsetseg, "Observed climate change in Mongolia," AIACC Working Paper No. 12, Washington, DC, USA, 2005. Available: http://www.aiaccproject.org
[9]. W. Feller, An Introduction to Probability Theory and Its Applications, 3rd ed. New York, NY, USA: Wiley, 1968.
[10]. M. Mood, F. A. Graybill, and D. C. Boes, Introduction to the Theory of Statistics, 3rd ed. New York, NY, USA: McGraw-Hill, 1974.
[11]. N. L. Johnson, S. Kotz, and N. Balakrishnan, Continuous Univariate Distributions, vol. 1, 2nd ed. New York, NY, USA: Wiley, 1994.
[12]. G. Casella and R. L. Berger, Statistical Inference, 2nd ed. Belmont, CA, USA: Duxbury Press, 2002.
[13]. J. F. Hair, W. C. Black, B. J. Babin, and R. E. Anderson, Multivariate Data Analysis, 8th ed. Andover, U.K.: Cengage Learning, 2019.
[14]. T. W. Anderson, "On the distribution of the two-sample Cramér-von Mises criterion," The Annals of Mathematical Statistics, vol. 33, no. 3, pp. 1148-1159, 1962. https://doi.org/10.1214/aoms/1177704477
[15]. K. Pearson, "Notes on regression and inheritance in the case of two parents," Proceedings of the Royal Society of London, vol. 58, pp. 240-242, 1895. https://doi.org/10.1098/rspl.1895.0041
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Erdenesuren Yadamsuren, Tseveennamjil Damiran
This work is licensed under a Creative Commons Attribution 4.0 International License.
Copyright on any research article in the Mongolian Journal of Agricultural Sciences is retained by the author(s).
The authors grant the Mongolian Journal of Agricultural Sciences a license to publish the article and identify itself as the original publisher.
Articles in the Mongolian Journal of Agricultural Sciences are Open Access articles published under a Creative Commons Attribution 4.0 International License CC BY.
This license permits use, distribution and reproduction in any medium, provided the original work is properly cited.
