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METAbarcoding for METAcommunities: towards a genetic approach to community ecology (META2)

Project
Understanding and predicting how biological communities respond to changing environments is a topic of prime concern for both science and society. Dispersal of organisms through space is a main driver shaping the structure of biological communities. It represents the foundational concept of most ecological theories aimed at understanding and explaining community assembly processes. Despite its importance, there is a scarcity of tools to measure how organisms of different species disperse through space and how successfully they are in colonising new habitats. This is especially true for non-charismatic biotic groups (i.e. insects), key organisms for the monitoring of environmental quality. The implementation of tools to effectively measure dispersal thus represents a top priority for planning efficient conservation strategies. Genetics proved to be very powerful in tracking the effect of dispersal on spatial and temporal trends of single species. However, it has not yet been embodied into community ecology practices due to technological limitations that impeded the sequencing of whole communities. META2 will solve this problem by developing an innovative framework based on metabarcoding, an emerging genetic technique that allows to infer species composition from organismal DNA of unknown samples. Central to this project is the notion of haplotype, a measure of relatedness among organisms that can be used to track species dispersal. Haplotypes inferred from metabarcoding will be used to build robust measures of spatial connectivity among communities. META2 will leverage on the concept of metacommunity, defined as a set of local communities linked by dispersal. Metacommunity is a core concept in community ecology and it is particularly suited to translate ecological theory into practical tools for conservation and biomonitoring purposes. This project holds great premises when considering the capacity of metabarcoding to provide information for dozens to hundreds of species simultaneously. META2 will thus represent a milestone forward in the way we survey and monitor biodiversity.
  • Overview
  • Skills
  • Research Outputs

Overview

Contributor

FRANCO VILLORIA Maria   Scientific Manager  

Representatives

DOCCHIO BRUGIONI Cecilia   Administrative  

Leading department

Marco Biagi Department of Economics   Principale  

Term type

PRIN Progetti di ricerca di rilevante interesse nazionale

Financier

Ministero dell'Università e della Ricerca
Funding Organization

Partner

Università degli Studi di MODENA e REGGIO EMILIA

Total Contribution (assigned) University (EUR)

75,721€

Date/time interval

October 5, 2023 - October 4, 2025

Project duration

24 months

Skills

Concepts (2)


LS8_1 - Ecosystem and community ecology, macroecology - (2022)

Settore SECS-S/01 - Statistica

Research Outputs

Research outputs (2)

Clustering Metabarcoding Data: a Model-Based Approach 
2025
Conference Paper
Clustering Metabarcoding Data: a Model-Based Approach 
2025
Conference Paper
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