functional traits, agroecology, functional ecology.

The Amazon rainforest contributes to climate change mitigation and impacts on the long-term hydrological and carbon balance. However, anthropogenic activities such as deforestation, intensification of agriculturalactivities, edge effects, fires and logging has been compromising the resilience of the forest and the provision of  ecosystem services. Agroforestry systems (SAFs), a consortium of woody plants and agricultural crops, are seen as a viable alternative to deforestation, helping to maintain part of the biodiversity, the functioning of ecosystems and the restoration of disturbed areas, as well as reflecting the traditional knowledge of local populations. Understanding how functional traits related to morphological, physiological, anatomical and phenological characteristics impact on the performance of individuals enables the planning of SAFs. In this way, the characteristics of the species and the functional diversity of the SAFs can influence the provision of the maximum potential ecosystem services in these carbon sequestration systems. This study aims to understand how functional diversity and ecological strategies vary in relation to the age of SAFs. To do this, we will test the following hypotheses: i) younger SAFs have more acquisitive functional traits in species and a lower rate of mycorrhizal association; ii) Functional diversity, uniformity and divergence is greater in older SAFs. This work will be carried out in the Chico Mendes Extractive Reserve, in Acre, in July 2024. Nine (9) SAFs of different ages will be evaluated, ranging from 2 years to 12 years. Considering all the cultivated species, 8 functional traits will be measured, from four individuals per species. The traits assessed will be root (specific root length; mycorrhizal association rate; root tissue density), stem (specific stem density) and leaf (specific leaf area; leaf dry mass content, leaf area). Functional diversity indices will be measured, the main ones being functional richness, functional uniformity and functional divergence. The traits and indices will be compared between SAFs of different ages using analysis of variance. Thus, this work will contribute to the understanding of how functional traits provide insights to guide the composition and management of species, which provide multiple functions in agroecosystems.