The Effects of Climate on the Distribution and Composition of Biological Soil Crusts: Insights from Drylands in China and Argentina

This project will quantify how climate affects biocrust abundance, composition, and diversity. By comparing independently fitted models from China and Argentina, we aim to determine climate's role in structuring these communities. We will integrate high-resolution climatic data with standardized field surveys to identify the optimal spatiotemporal resolution for these relationships. We consider that using multiple spatial and temporal scales, rather than a single database, will allow us to better define climate-related biocrust patterns

Biocrust Genetic Diversity and Climatic Fingerprint 

The main objective of this project is to understand the effect of climate on biocrust genetic diversity and to project changes in biocrust diversity under future global change scenarios. To achieve this, we propose integrating high-spatiotemporal resolution climatic data with metagenomic data. By defining a climate fingerprint, we expect to enhance our understanding of current biocrust distribution patterns and to project changes under future climate scenarios

Biological Soil Crusts, the Living Skin of Soils that Alleviates the Effects of Desertification in Drylands

In this project, our overarching goal is to study the response of biological soil crusts to changes in land use (biotic stress) and climate change (abiotic stress) in arid and semi-arid ecosystems using the diversity of drylands in Argentina as a natural laboratory

Microbial Diversity of the Argentinean Sea within the Global Ocean

Under construction!!!

Fertility and Biological Soil Crusts in Drylands: the Effects of Land Use and Climate Change Towards a Sustainable Development Goal

Our general research objective is to understand the structure and functioning of biological soil crusts under current and future climatic and land use conditions. Understanding the interactive effects of land use changes and climate change on biocrusts is essential to better predict potential changes in the productivity of drylands as a consequence of desertification processes mediated by the loss in soil fertility under current and future conditions