Agroforestry systems as an alternative for the restoration of the biological potential of Amazonian soils

Abstract

The Amazon has one of the most biodiverse biomes in the world and plays an essential role in global climate regulation. However, the expansion of agricultural activity in the region has led to soil degradation and loss of biodiversity in large portions of the biome. The loss of plant native cover caused by deforestation and the increasing exposure of the region's highly weathered and infertile soils to the action of the tropical climate has led to the erosion and loss of the superficial organic layer, with subsequent loss of soil fertility. This loss of fertility and subsequent yield reduction after deforestation leads to the abandonment of large areas for natural regeneration, making the agricultural production model in the region unsustainable. For this, agroforestry systems (SAFs) have been suggested as an alternative for sustainable production in the Amazon. The present project proposes the study of the soil health of agroforestry systems in a time and diversity gradient through the analysis not only of the physicochemical but also of biological parameters such as the enzymatic activity of the soil (²-glucosidase, acid phosphatase, and arylsulfatase) and the abundance of bacteria, archaea, and fungi, in order to represent the main functions and ecosystem services provided by the soil as evidenced by the high productivity observed in the systems over time by producers in the region of Tomé-Açu (PA). The study seeks to merge modern techniques used in soil science with next-generation DNA sequencing of the bacteria, archaea, and fungi communities associated with the litter and the different soil layers for a multidimensional analysis of soil quality from an agronomic and biological point of view. Measurement of carbon stocks of the different fractions of the organic matter will also be carried out to verify the ability to sequester and stabilize carbon over time. We also expected to identify changes in the structure and composition of microbial communities of bacteria, archaea, and fungi along the time and diversity gradient for the identification of key microorganisms for the execution of the main functions and ecosystem services.