Crop functional structure predicts the provision of Nature´s material Contribution to People in diversified agroforestry

Abstract

Applying concepts from natural ecosystem ecology, particularly through diversified cropping systems that integrate woody crops with other crops, can enhance agrobiodiversity and significantly contribute to multifunctional agriculture. The ecological and, more recently, the agronomic literature have indicated that functional trait aspects of diversity offer a more comprehensive explanation for ecosystem functions compared to species richness alone. In this study, we apply the trait-based approach during experimental agroforest succession in subtropical Southern Brazil to investigate the main factors of crop functional structure, differentiating the effects of functional diversity (FD) from functional identity (CWM - community weighted mean), on Nature's Contributions to People (NCP). The experiment was designed varying crop FD, based on leaf nitrogen concentration, while maintaining crop species richness constant across all treatments. To assess FD and CWM, we measured six crop traits; maximum plant height, leaf area, specific leaf area, leaf nitrogen content, leaf dry-matter content, and stem-specific density. Additionally, we evaluated four material NCP (green manure, forage, germplasm, and food) based on data collected during the initial four years of the experiment (2017–2020). To analyze the data, we employed principal component analysis to reduce the number of variables and subsequently fitted linear mixed-effect models. Our findings provide support for the hypothesis that crop functional structure, particularly in relation to leaf traits (leaf area and leaf nitrogen content) and vegetative height, significantly influences material outputs and predicts above-ground biomass production that can be utilized as green manure and animal feed in agroforestry and silvopastoral systems. Both FD and CWM were important drivers of NCPs, showing that both niche complementarity and selection effects contribute to explain agroecosystem functioning. By utilizing functional traits, we reached valuable insights for generating agronomical recommendations and enhancing cropping system diversification through effective trait-based management.