Elucidating the impact of carbon dioxide enhancement on fungal and fungal-like plant pathogen dynamics

General project description (<400 words)
It is well established that fungal communities respond to changes in climate by altering overall abundance and progression through their developmental cycle. Recent research on the effect of long-term elevated CO2 on fungal communities in a controlled grassland ecosystem found significant changes in fungal community structure. In boreal forest soils, increased temperatures also led to changes in mycobiome composition.

In boreal ecosystems, this might be beneficial in the context of fungal communities that contribute to carbon cycling as decomposers of organic matter freeing carbon and other nutrients within ecosystems. At the same it might also lead to the emergence of fungal and fungal-like plant pathogens. For example, oak species dominate the UK's lowland woods and, like many native trees, are under threat from emerging pests and disease, particularly oak processionary moth (OPM) and acute oak decline (AOD). These new pests and diseases act alongside more established environmental stresses that are often associated with climate change. They add to the constant pressure of established/endemic threats such as oak mildew and honey fungus.

This clearly demonstrates the need for an in-depth understanding of CO2-induced changes of the forest mycobiome structure in order to develop strategies to circumvent the potential negative ecological and socioeconomic impacts of fungal and fungal-like plant pathogens.

Therefore, we are proposing this project to elucidate the effect of elevated CO2 in mycobiome structure and diversity in correlation with environmental variables in a forest ecosystem, the University of Birmingham's BIFoR Free Air Carbon Dioxide Enrichment (FACE) facility (http://www.birmingham.ac.uk/research/activity/bifor/index.aspx). We will employ a combined target candidate and unbiased sequencing approach to 1.) characterise fungal and fungal-like plant pathogen availability, 2.) elucidate the plant response to fungal and fungal-like pathogen attack and 3.) model the long-term impact of CO2 enhancement on fungal and fungal-like plant pathogen availability.

In summary, this proposal will provide essential information on the current health of UK oak woodlands and enable predictions of potential future impacts fungal and fungal-like plant pathogens. This will provide a traffic-light tool kit alerting for potential fungal and fungal-like plant pathogen outbreaks based on high risk environmental conditions. In the long-term, this will enable the development of strategies to mitigate ecological and socioeconomic impacts caused by fungal and fungal-like plant pathogens.


Alignment with core DREAM themes of Big Data, Risk and Mitigation (<400 words),

BIG DATA: Our approach will create large metagenomic data sets from triplicate sampling on a monthly basis for two years, each covering almost 1000 operational taxonomic units, to create networks on a temporal-spatial scale. In combination with extensive routinely collected continuous high-resolution metadata (taken every minute) from over ten distinct data streams from multiple locations (e.g. atmospheric, hydrological, meteorological) we will model the long-term risks of fungal and fungal-like plant disease. This will provide over 100 million unique data points. We will develop methodologies to establish clustering algorithms to ensure scientific relevant data mining outputs. These datasets will also be of great value to the greater research community. We will make all data sets available to the research community for further data mining as soon as feasible.