Maximum entropy approach as a tool to predict arbuscular mycorrhizal fungi (AMF) distribution in soils of Argentinean Puna

NEPOTE VALENTIN, DAVIDE; VOYRON, SAMUELE; SOTERAS, FLORENCIA; ONTIVERO, R EMANUEL; IRIARTE, HEBE J.; GIOVANNINI, ANDREA; RISIO ALLIONE, LUCÍA; LUMINI, ERICA; LUGO, MÓNICA A.

Leticia

Simposio; III International Symposium on Mycorrhizal Symbiosis in South America; 2023

UNAL - SINCHI

The biogeographic region of Argentinean Puna extends at elevations higher than 3,000 m within the Andean Plateau and hosts diverse ecological communities adapted to aridity, low temperatures and poorly evolved soils. Geomorphology is shaped by drainage networks, often resulting in hypersaline endorheic basins known as salar. Local communities rely on soil fertility for agricultural practices and on pastures for livestock rearing. Exploring the scarcely studied microbiological diversity of these soils as indicators of ecosystems functioning might help to predict the fragility of these harsh environments. In this study we collected 28 soil samples from three typical landscapes: Puna grassland, hypersaline salar and family-run cropfields. Total fungi and AMF occurrence were analyzed using eDNA metabarcoding sequencing. We performed Species Distribution Modeling (SDM) within an environmental coherent area to predict AMF suitability in the different macro-habitats. Through a maximum entropy approach, we created maps of environmental suitability for AMF distribution. The SDM predicted lower suitabilities in hypersaline salar areas, while grassland habitats and a wider range of temperature seasonality were significantly related to AMF enrichment.To assess the impact of farming on AMF occurrence (extremely abundant in cropfields), we set a new model excluding the cultivated areas. We observed that if the cultivated areas had remained unmanaged, the large-scale soil features and local bioclimatic constraints would likely have led to lower AMF suitability. Using SDM we evidenced the influence of bioclimatic, edaphic and anthropogenic factors in shaping AMF occurrence. Additionally, we highlighted the relevance of human activities in accurately predicting AMF distribution.