@article{article_1687349, title={ANALYSIS OF FOREST CONSERVATION PERFORMANCE OF MAJOR FORESTED COUNTRIES: AN APPLICATION USING TOPSIS AND WASPAS}, journal={Turkish Journal of Forest Science}, volume={9}, pages={313–338}, year={2025}, DOI={10.32328/turkjforsci.1687349}, author={Altıntaş, Furkan Fahri}, keywords={ÇKKV, WASPAS, TOPSIS, çevresel performans endeksi, orman koruma performansı.}, abstract={Countries hosting extensive forest areas, particularly those encompassing a significant proportion of the world’s forests, play a critical role in global biodiversity, environmental stability, and economic systems. Within this framework, the forest conservation performance of nine nations—Russia, Brazil, Canada, the USA, China, the Democratic Republic of Congo (DRC), Indonesia, India, and Peru—representing 65% of global forest cover, was evaluated using the 2024 Forest Environmental Performance Index (EPI-F) criteria through the WASPAS (Weighted Aggregated Sum Product Assessment) and TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) methodologies. Results indicated that rankings derived from WASPAS and TOPSIS diverged only for China and India. Furthermore, average forest conservation performance scores were computed using both approaches. According to WASPAS, India, China, and Peru exceeded the average, whereas TOPSIS identified India, China, Peru, and Indonesia as above-average performers. Consequently, a joint evaluation of both methods suggests that Russia, Brazil, Canada, the USA, the DRC, and Indonesia, whose forest conservation performances fall below the average, should reinforce their conservation policies to more effectively support global environmental integrity, biodiversity preservation, and economic sustainability. Moreover, sensitivity and comparative analyses confirmed the suitability of WASPAS and TOPSIS within the EPI-F framework for assessing these countries’ forest conservation performance. Regarding limitations, the study exclusively employed data from 2024. Future research may benefit from longitudinal analyses spanning multiple years and incorporating additional multi-criteria decision-making (MCDM) techniques to broaden the methodological comparison.}, number={2}, publisher={Kahramanmaraş Sütçü İmam Üniversitesi}