Exploring liana-driven vertical complexity using GEDI simulator and Lorenz-entropy in a neotropical dry forest

• Lianas significantly elevate Lorenz-entropy values in intermediate and late stages. • Combining LiDAR and GEDI simulation enhances liana detection at plot scale. • Early-stage non-infested plots exhibit greater entropy due to canopy gaps. Lianas play a crucial role in shaping the vertical structural complexity of tropical forests; however, their impact is not well understood. This study evaluates the influence of lianas on the Lorenz-entropy (LE) index, a measure of canopy heterogeneity, in a Neotropical tropical dry forest (TDF) in Santa Rosa National Park, Costa Rica. Using full-waveform LiDAR data and simulated Global Ecosystem Dynamic Investigation (GEDI) waveforms, we compared liana-infested and non-infested plots across early, intermediate, and late successional stages. Using Mann-Whitney U test with Benjamini-Hochberg (BH) correction (95 % confidence level) our findings indicate that liana-infested plots exhibit significantly higher Lorenz-entropy index values in intermediate (P< 0.05 , P < BH-threshold), and late (P < 3.33 × 10 - 2 , P < BH-threshold) successional stages, while early-stage in non-infested plots showed significantly higher entropy values (P< 1.67 × 10 - 2 , P < BH-threshold). Effect size analysis showed a moderate impact in the intermediate stage (Cliff’s δ = 0.35, 95 % CI: 0.07–0.61) and a moderate to large impact in the late stage (Cliff’s δ = 0.41, 95 % CI: 0.11–0.67). In early-stage plots, liana-infested stands had significantly lower LE index values than non-infested plots (Cliff’s δ = –0.50, 95 % CI: –0.78 to –0.19). These results demonstrate that the LE index effectively captures liana-driven increases in vertical canopy stratification and heterogeneity, particularly in more mature forest stages. The integration of airborne LiDAR and GEDI simulations offers an approach for assessing structural complexity at the plot level. These findings highlight the need for further research to understand the long-term ecological consequences of liana abundance, in the context of forest monitoring.