Final Report Summary - MP-ALPS (Examination of the relationship between microbial and plant diversity across large spatial and elevational gradients to predict community migration patterns as a function of climate change)
The main goal of the Marie Curie fellowship MP-Alps (2011-2013) was to study the biogeography of soil microorganisms within a 700 km2 region of the Western Swiss Alps in relation to possible climate change. The idea of the project was to analyze microbial diversity across a wide range of sampling sites, for which exhaustive data were already available as far as plant diversity, chemical and soil parameters, and macrofauna. The combination of data sets would then allow to use statistical models that can predict distribution of microorganisms across the alpine landscape as a function of aboveground plant communities, and perhaps as a result of climate and land use changes. The project focused on using state-of-the-art ultra-high throughput sequencing technology as tool for microbial community analysis. The project developed along two axes: (i) the development of a suitable pipeline for community analysis based on Illumina HiSeq sequencing, (ii) field sampling campaigns and analysis of the microbial diversity in those sites over 3 years. The MP-Alps project was embedded in a larger project team studying biodiversity in this area.
A trial small field campaign was carried out in the fall of 2011, in order to to develop an appropriate field soil sample collection and processing protocol, to standardize DNA isolation protocols, as well as developing and optimizing the molecular biology protocols (primers, PCR, library preparations) required to process DNA samples prior to Illumina sequencing. Primer sets were developed to target most of the Bacteria and Archaea, and which would enable multiplexing on Illumina HiSeq (allowing multiple samples to be mixed in one "flow lane"). A bioinformatics pipeline was written in Bash scripting language in order to automate the process of demultiplexing the DNA sequencing reads afterwards and filtering out anomalous sequences. Statistics-based microbial community analysis of the sequences from the 2011 soil samples revealed that the developed protocols gave reliable results that could replicate trends in the soil microbial communities that have been previously documented in published literature. Two large field campaigns were carried out in the summers of 2012 and 2013. More than 300 soil samples were collected and processed for use in the above described objectives. In order to determine the level of temporal variability at sampling sites, we sampled 16 field sites three times over the course of a single summer.
A total of 112 and 228 samples from 105 and 195 sites were collected during the summers of 2012 and 2013, respectively. Data from the 2013 sampling campaign were not available at the time of writing this report because the field campaign ended only in September 2013. Analysis of the 2012 samples showed that the alpine soil bacterial communities are most strongly influenced by soil pH, with 24.6% of the total variation in the community structure being explained by pH. The sites could also be distinguished into two categories, the grassland type sites with low to neutral pH and the alpine type sites with a pH range that was significantly higher than in the grasslands. 9.2% of the variation was explained by elevation. Further analysis will be done to determine the effect of soil chemical components and plant composition on soil bacterial communities when the data become available.
Final results will include implementation of spatial distribution models to model the microbial communities patterns across the alpine landscape. This will begin after all of the empirical data have been analyzed and the effect of the various biotic and abiotic factors are determined. Once the models are optimized, they will be used to predict microbial migration patterns as a function of climate and land use changes in the alpine ecosystem. This can then be used as further basis for political decisions on alpine landscape use. A number of draft manuscripts have been outlined, which will be submitted in the coming 1-2 years. Continuation of the project by the MC fellow was guaranteed through a specific grant that promotes women-with-small-children careers in research ("Pro-Femmes"). A variety of new collaborations was started, which link the project to a larger scale biodiversity analysis study and to soil chemistry studies in the same area.
A trial small field campaign was carried out in the fall of 2011, in order to to develop an appropriate field soil sample collection and processing protocol, to standardize DNA isolation protocols, as well as developing and optimizing the molecular biology protocols (primers, PCR, library preparations) required to process DNA samples prior to Illumina sequencing. Primer sets were developed to target most of the Bacteria and Archaea, and which would enable multiplexing on Illumina HiSeq (allowing multiple samples to be mixed in one "flow lane"). A bioinformatics pipeline was written in Bash scripting language in order to automate the process of demultiplexing the DNA sequencing reads afterwards and filtering out anomalous sequences. Statistics-based microbial community analysis of the sequences from the 2011 soil samples revealed that the developed protocols gave reliable results that could replicate trends in the soil microbial communities that have been previously documented in published literature. Two large field campaigns were carried out in the summers of 2012 and 2013. More than 300 soil samples were collected and processed for use in the above described objectives. In order to determine the level of temporal variability at sampling sites, we sampled 16 field sites three times over the course of a single summer.
A total of 112 and 228 samples from 105 and 195 sites were collected during the summers of 2012 and 2013, respectively. Data from the 2013 sampling campaign were not available at the time of writing this report because the field campaign ended only in September 2013. Analysis of the 2012 samples showed that the alpine soil bacterial communities are most strongly influenced by soil pH, with 24.6% of the total variation in the community structure being explained by pH. The sites could also be distinguished into two categories, the grassland type sites with low to neutral pH and the alpine type sites with a pH range that was significantly higher than in the grasslands. 9.2% of the variation was explained by elevation. Further analysis will be done to determine the effect of soil chemical components and plant composition on soil bacterial communities when the data become available.
Final results will include implementation of spatial distribution models to model the microbial communities patterns across the alpine landscape. This will begin after all of the empirical data have been analyzed and the effect of the various biotic and abiotic factors are determined. Once the models are optimized, they will be used to predict microbial migration patterns as a function of climate and land use changes in the alpine ecosystem. This can then be used as further basis for political decisions on alpine landscape use. A number of draft manuscripts have been outlined, which will be submitted in the coming 1-2 years. Continuation of the project by the MC fellow was guaranteed through a specific grant that promotes women-with-small-children careers in research ("Pro-Femmes"). A variety of new collaborations was started, which link the project to a larger scale biodiversity analysis study and to soil chemistry studies in the same area.