Morphological Traits as Predictors of Litter Decomposition in Agroforestry Tree Species of Rwanda

Abstract

This study examines the influence of key morphological traits and how the leaf traits are essential for understanding the strategies of  biomass decomposition at the leaf trait level. Leaf thickness, leaf area, specific leaf area, and leaf dry matter content were morphological traits, and lignin and tannin were quality traits affecting litter decomposition, measured across six agroforestry tree species. We applied  linear mixed models to quantify the effects of these traits on decomposition, treating species as random effects to account for  interspecies variability. Principal Component Analysis revealed that the first principal component, which explains 45.6% of the total  variance, is strongly associated with leaf thickness and dry matter content. These traits emerged as the primary drivers of variance in litter decomposition rates. The second principal component, accounting for 26.4% of the variance, is primarily influenced by Leaf Area  and Lignin content, indicating their significant roles in the secondary variation observed among species. The total linear mixed model,  incorporating all morphological traits, provided a significantly better fit than the reduced model, as indicated by a Chi-square test (p <  0.05). This suggests that combining morphological traits is crucial for understanding litter decomposition dynamics. Moreover, the results  highlight species-specific differences in trait effects, emphasizing the need for tailored management strategies in agroforestry  systems to optimize nutrient cycling. These findings contribute to a deeper understanding of the factors influencing litter decomposition,  offering practical insights for selecting tree species that enhance soil fertility through improved decomposition rates. The study  underscores the importance of considering both trait variability and species identity to optimize agroforestry practices for sustainable  land management.