Metabarcoding of arthropod communities as biomonitoring tool for the conservation

Abstract

Deforestation and fragmentation of forests contributes to dramatic loss of biodiversity and ecosystem services. As a strategy to combat this degradation, it has been proposed to recover deforested areas through forest plantations and to perform sustainable forestry as an alternative to illegal logging. For example, these strategies are part of the arguments used to change the type of natural protected area of the Nevado de Toluca Park, in Mexico. Although plantations and sustainable forestry ensure the persistence of the tree cover, these involve anthropogenic changes and disturbances, whose effects on fauna communities and biodiversity evolution are poorly known. To study these effects from an ecological perspective and to provide effective management recommendations data on species' distribution and abundance over large geographic and temporal scales is needed. Here, we perform arthropod biomonitoring of Nevado de Toluca forests lands subjected to conservation or different types of forestry, to examine changes at the biological community level. For this, we sampled around 3,000 pitfall traps during 15 days of the main rain season. These were subjected to metabarcoding (COI gene) sequencing for operational taxonomic units (OTUs) identification. We focus in the arthropods-community as bio-indicator, joining the community structure (diversity, abundance and richness) with the estimators of biological diversity (indices of diversity: abundance and species richness) to describe the behavior of arthropods-communities under different environmental and management conditions. Metabarcoding allowed to identify OTUs and describe communities with a resolution not feasible by traditional methods, due to the poor taxonomic knowledge of the area. When then analyses how components of Gamma diversity (regional pool of species = landscape), Alpha diversity (local pool) and Beta diversity (replacement/ turnover) between communities vary according to the different types of forest land conditions. We conclude arthropod metabarcoding is a reliable and informative biomonitoring tool that allowed to better understand the impact of forest management on arthropods communities.