A conceptual framework and experimental design for analysing the relationship between biodiversity and ecosystem functioning (BEF) in agroforestry systems

Abstract

There is compelling evidence for positive effects of plant diversity on the functioning of forests and agroecosystems. This information is increasingly used to optimize production systems that provide a wide range of ecosystem services. While agroforestry is actively promoted for the sustainable intensification of agriculture and restoration of degraded landscapes, there is a paucity of knowledge on Biodiversity Ecosystem Functioning (BEF) relationships in agroforestry systems. Since BEF-relationships in agroforestry might be shaped by combinations of different life-forms (e.g. trees, shrubs, herbs) and their interactions, experiences from grassland and forest experiments cannot be readily transferred to agroforestry. This highlights the need for a new type of experiments in agroforestry to advance our understanding of the role of biodiversity for the functioning of these systems. Therefore, our aim was to develop a conceptual framework for analysing BEF-relationships in agroforestry systems and to present an exemplary design for this purpose, which we placed in a (sub)tropical context. Based on designs used in tree diversity experiments, we suggest four major design principles: 1) a trait-based approach for selecting tree and crop species, 2) the integration of trees and crops along a gradient of functional diversity, 3) maintaining constant density across different combinations of life-forms in agroforests through the concept of “growing-patch-density”, and 4) disentangling a priori the effects of species diversity on ecosystem functioning from those of structural and functional diversity, defined here as the variation in structural attributes such as plant dimensions and in plant functional traits, respectively. Our conceptual design and the embedded principles offer a promising avenue to identify important drivers of specific BEF-relationships and to quantify management influences on these. This design can support new research projects that aim at improving ecosystem functioning of agroforestry with the view of optimizing the provision of ecosystem services and facilitation of ecosystem restoration.