TR
EN
Statistical analysis in R for environmental monitoring using FAO dataset
Abstract
Nature protection practices and agricultural systems face sustainability challenges in mountainous countries regions with limited resources. The dynamics between agriculture and nature involves complex interactions that reflects the responses of farming systems to shifts in nature conservation policy and biophysical factors. Moreover, climate change impacts biodiversity through control of water resources and soil fertility. In Italy, mountain areas have experienced socio-economic changes in recent decades, which has affected traditional agro-forestry activities and resulted in forest expansion. This study examines the sustainability performance of farming systems and forest protection areas in Italy. Existing FAO data on 1990-2025 were used to analyse the dynamics in land use and land cover (LULC) changes in context of social-economic, climate and environmental aspects. The data analysis was performed using R language by its statistical and computing libraries such as readr, ggplot2, reshape2, tidyverse, gridExtra, stats, plotly, latticeExtra, ggpubr as the main ones. The results demonstrated trends in reforestation (increase of forest areas on 9% and shrubland on 21%), climate warming (glacier and snow retreat on 34%), urbanization (increease of artificial surfaces on 5.8 %) and intensification of agriculture activities (stable increase in cropland on 2 %), which indicates sustainable development in nature protection and social-economic activities of Italy.
Keywords
References
- Allegrezza, M., Tesei, G., Francioni, M., Giovagnoli, D., Bianchini, M., & D’Ottavio, P. (2025). The Effects of Different Management Intensities on Biodiversity Conservation in the Wooded Grasslands of the Central Apennines. Forests, 16(7), 1034. https://doi.org/10.3390/f16071034
- Altieri, M. A. (1999). The ecological role of biodiversity in agroecosystems. Agriculture, Ecosystems and Environment, 74(1–3), 19–31. https://doi.org/10.1016/S0167-8809(99)00028-6
- Altieri, M. A., Nicholls, C. I., Henao, A., & Lana, M. A. (2015). Agroecology and the design of climate change-resilient farming systems. Agronomy for Sustainable Development, 35(3), 869–890. https://doi.org/10.1007/s13593-015-0285-2
- Anđelković, A., & Radulović, S. (2022). The role of riparian areas in alien plant invasions. Acta herbologica, 31(2), 93-104. https://doi.org/10.5937/actaherb2202093A
- Arcidiaco, L., & Corongiu, M. (2025). Analysis of LULC Change Dynamics That Have Occurred in Tuscany (Italy) Since 2007. Land, 14(3), 443. https://doi.org/10.3390/land14030443
- Batáry, P., Dicks, L. V., Kleijn, D., & Sutherland, W. J. (2015). The role of agri-environment schemes in conservation and environmental management. Conservation Biology, 29(4), 1006–1016. https://doi.org/10.1111/cobi.12536
- Baumer, B., Cetinkaya-Rundel, M., Bray, A., Loi, L., and Horton, N. J. (2014). R Markdown: Integrating a Reproducible Analysis Tool Into Introductory Statistics. Technology Innovations in Statistics Education, 8, 1–22. https://doi.org/10.5070/T581020118
- Be, M. C., Randrianantenaina, A. S., Kanneh, J. E., Han, Y., Lei, Y., Zhi, X., Xiong, S., Jiao, Y., Shang, S., Ma, Y., Yang, B., Tao, L., & Li, Y. (2025). Comparative Analysis of Machine Learning Algorithms for Object-Based Crop Classification Using Multispectral Imagery. Drones, 9(11), 763. https://doi.org/10.3390/drones9110763
Details
Primary Language
English
Subjects
Regional Geography
Journal Section
Research Article
Authors
Publication Date
April 25, 2026
Submission Date
September 3, 2025
Acceptance Date
November 22, 2025
Published in Issue
Year 2026 Number: 5
APA
Lemenkova, P. (2026). Statistical analysis in R for environmental monitoring using FAO dataset. Journal of Anatolian Geography, 5. https://doi.org/10.65652/jag.1777704
AMA
1.Lemenkova P. Statistical analysis in R for environmental monitoring using FAO dataset. JAG. 2026;(5). doi:10.65652/jag.1777704
Chicago
Lemenkova, Polina. 2026. “Statistical Analysis in R for Environmental Monitoring Using FAO Dataset”. Journal of Anatolian Geography, nos. 5. https://doi.org/10.65652/jag.1777704.
EndNote
Lemenkova P (April 1, 2026) Statistical analysis in R for environmental monitoring using FAO dataset. Journal of Anatolian Geography 5
IEEE
[1]P. Lemenkova, “Statistical analysis in R for environmental monitoring using FAO dataset”, JAG, no. 5, Apr. 2026, doi: 10.65652/jag.1777704.
ISNAD
Lemenkova, Polina. “Statistical Analysis in R for Environmental Monitoring Using FAO Dataset”. Journal of Anatolian Geography. 5 (April 1, 2026). https://doi.org/10.65652/jag.1777704.
JAMA
1.Lemenkova P. Statistical analysis in R for environmental monitoring using FAO dataset. JAG. 2026. doi:10.65652/jag.1777704.
MLA
Lemenkova, Polina. “Statistical Analysis in R for Environmental Monitoring Using FAO Dataset”. Journal of Anatolian Geography, no. 5, Apr. 2026, doi:10.65652/jag.1777704.
Vancouver
1.Polina Lemenkova. Statistical analysis in R for environmental monitoring using FAO dataset. JAG. 2026 Apr. 1;(5). doi:10.65652/jag.1777704