Biomass estimation and relationships with taxonomic diversity and functional trait: insights from exclosure areas in the north-eastern Ethiopian highlands

Abstract

There is paucity of empirical evidences regarding carbon balance and quantifications in tropical forest ecosystems. Yet precise estimation of biomass and forest carbon stock is crucial for carbon budget accounting and monitoring. Here, we estimated the biomass of woody species using forest inventory data from 185 plots with different forest exclosure ages and evaluated relationships with taxonomic diversity and community weight mean (CWM). We used a generalized linear mixed-effects model (GLMMs) to examine changes in biomass contents across forest exclosure ages. Besides, structural equation model (SEM) was employed to assess the direct and indirect impacts of taxonomic diversity and functional trait on AGB. Our findings indicated that woody species AGB, belowground biomass (BGB), and total carbon stock (TCS) increased significantly (p < 0.001) with increasing forest exclosure ages. However, a decreasing trend AGB was observed over twenty years of exclosure. The structural equation models (SEMs) revealed that community weight mean (CWM) (β = 0.07 to 0.28) and Shannon diversity (β = 0.01 to 0.32) positively related to aboveground biomass across all study forest exclosure sites, whereas CWM (β = -0.28) had a significant negative effect on AGB in the open woodland area. The study found that species richness did not (β = −0.21 to −0.41) direct effect on aboveground biomass (AGB). However, the impact of richness on aboveground biomass was mediated through the species diversity. The overall SEM model also showed that AGB had positive link with diversity and forest exclosure ages, but a negative correlation with species richness (β = -0.02) and CWM (β = -0.12). Our results elucidated the importance of varying forest exclosure ages on biomass accumulation and carbon-biodiversity relationships, which are important for identifying essential species and carbon stock for conservation under climate change scenarios.