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Accurate measurements of methane (CH 4 ) and carbon dioxide (CO 2 ) fluxes from tree stems are important for understanding greenhouse gas emissions. Closed chamber methods are commonly employed for this purpose; however, leaks between the chamber and the atmosphere as well as gas accumulation, known as the concentration buildup effect, can impact flux measurements significantly. In this study, we investigated the impacts of concentration buildup and leaks on semi-rigid closed chamber methods. Field measurements were conducted on six tree species, including three species from a Mexican mangrove ecosystem and three species from a Magellanic sub-Antarctic forest. Systematic observations revealed significant leak flow rates, ranging from 0.00 to 465 L h -1 , with a median value of 1.25 ± 75.67 L h -1 . We tested the efficacy of using cement to reduce leaks, achieving a leak flow rate reduction of 46-98 % without complete elimination. Our study also demonstrates a clear and substantial impact of concentration buildup on CH 4 flux measurements, while CO 2 flux measurements were relatively less affected across all tree species studied. Our results show that the combined effects of leaks and concentration buildup can lead to an underestimation of CH 4 emissions by an average of 40 ± 20 % and CO 2 emissions by 22 ± 22 %, depending on the bark roughness. Based on these findings, we recall a straightforward yet effective method to minimize experimental errors associated with these phenomena, previously established, and reiterated in the current context, for calculating emissions that considers effects of leaks and concentration buildup, while eliminating the need for separate determinations of these phenomena. Overall, the results, combined with a literature review, suggest that our current estimates of GHG flux from tree stems are currently underestimated., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)