Taiwan hinoki (Chamaecyparis obtusa Sieb. & Zucc. var. formosana (Hayata) Rehder) is one of the dominant coniferous species in subtropical montane cloud forests in Taiwan, with a high affinity for fog immersion. With the changing climate, the species is expected to face new environmental challenges. Identifying stress factors affecting species regeneration is therefore crucial for understanding how the species would be affected by future climatic scenarios. Our study quantified seedling performance by biomass increment to identify the effect of key ecological factors, namely short-duration drought (watering every 4, 8, 12 days), type of substrate (forest soil and coarse wood debris [CWD]), and bryophyte carpet, on seedlings’ early-stage performance. Furthermore, we explored both morphological and physiological traits to unveil possible adaptation strategies. The results revealed that bryophyte carpets accumulated nutrient-rich humus, which reduced the nutrient regime difference between CWD and soil. Short-duration drought was confirmed to be a stress factor for the seedlings, particularly under prolonged drought scenario, whereas the drought mitigation ability of CWD and bryophyte carpet was weaker than expected. By considering the field observation, we concluded that the bryophytes carpet with humus accumulation on CWD, but not the CWD itself, facilitates the seedlings’ regeneration. Furthermore, prolonged drought under climate change could pose a potential threat to the seedlings in their early stages, adversely affecting regeneration.

When understanding how intraspecific trait variation (ITV) responds to plot-level environmental gradients at the community scale, studies often overlook within-plot environmental heterogeneities, particularly light variation along the vertical profile of vegetation. This omission can lead to inaccurate estimations of ITV-environmental relationships. Currently, there is no proper analytical framework to address this gap. To address this issue, we propose a conceptual framework that integrates both plot- and within-plot-level environmental factors to analyze ITV-environmental relationships, emphasizing the use of plant individuals as study units and appropriate upscaling to the community scale through a robust sampling design. Furthermore, we applied the proposed framework to empirical data from a subtropical montane cloud forest to reveal the responses of traits from chronic wind stress and light exposure. Our framework can be implemented within a mixed-effects model without substantial drawbacks in terms of statistical power or Type I error rates, as demonstrated by our performance analysis on simulated data. Application to empirical data from a subtropical montane cloud forest further shows that neglecting within-plot light variation may obscure our understanding of plant adaptations to plot-level chronic wind stress. Across response traits, we observed consistent adjustments to light exposure, with more conservative trait expressions in higher light regimes. After accounting for the light effect, both leaf thickness and specific leaf area (SLA) continued to respond to wind stress, but the wind effects were dramatically reduced, especially in SLA. Overall, our results demonstrate that incorporating within-plot environmental variation is critical to accurately quantify ITV–environment relationships and may provide new insights into plant adaptive strategies in trait ecology.