Uncovering Seasonal Heterogeneity in Forest Ecosystem Valuation: Evidence from a Meta-Analysis with Experimental Insights

Seasonal variation not only influences the ecological functioning of forest ecosystems but also alters the benefits people derive from them, ranging from physical to psychological restoration. Ignoring such variation in valuation risks, thereby producing seasonally biased and unreliable estimates, constitutes an issue that previous valuation studies have largely overlooked. This study investigates the extent of seasonal bias in willingness to pay (WTP) for forest ecosystem services using a meta-dataset of 476 observations from Korea. Applying pooled, weighted, and robust mixed-effects models, we uncovered substantial seasonal heterogeneity through our analysis: WTP increases by 67% in autumn but declines by 18% and 65% in the summer and winter, respectively. The robust mixed-effects model provided the best empirical fit, highlighting the methodological value of explicitly modeling temporal effects in meta-regression. These results reflect seasonally differentiated engagement with forests and suggest that individuals implicitly recognize the temporal value of ecosystem services. Nevertheless, limitations remain, particularly the heterogeneity of research designs, survey methods, and elicitation formats, which may introduce variability and potential bias. Therefore, while seasonal differences are statistically significant, the results should be interpreted with caution. Extrapolating annual values from single-season data risks systematic distortion, especially when stated preference methods are used. Beyond methodological implications, the findings also underscore a broader point: seasonal rhythms shape not only ecosystem dynamics but also human well-being. Accurately valuing these shifting benefits is essential for making credible economic assessments and sustaining long-term reciprocity between people and nature.