Earthworms are known for their important role within the functioning of an ecosystem, and their diversity can be used as an indicator of ecosystem health. To date, earthworm diversity has been investigated through conventional extraction methods such as handsorting, soil washing or the application of a mustard solution. Such techniques are time consuming and often difficult to apply. We showed that combining DNA metabarcoding and next-generation sequencing facilitates the identification of earthworm species from soil samples. The first step of our experiments was to create a reference database of mitochondrial DNA (mtDNA) 16S gene for 14 earthworm species found in the French Alps. Using this database, we designed two new primer pairs targeting very short and informative DNA sequences (about 30 and 70 bp) that allow unambiguous species identification. Finally, we analysed extracellular DNA taken from soil samples in two localities (two plots per locality and eight samples per plot). The two short metabarcode regions led to the identification of a total of eight earthworm species. The earthworm communities identified by the DNA-based approach appeared to be well differentiated between the two localities and are consistent with results derived from inventories collected using the handsorting method. The possibility of assessing earthworm communities from hundreds or even thousands of localities through the use of extracellular soil DNA will undoubtedly stimulate further ecological research on these organisms. Using the same DNA extracts, our study also illustrates the potential of environmental DNA as a tool to assess the diversity of other soil-dwelling animal taxa.

seasonal trend, with a higher ratio in winter than in summer, suggesting that the seasonal shift in MCS is accompanied by a change in their activities. Surprisingly, we observed a significant decrease in soil organic carbon (SOC) concentration after four years of soil transplantation, as compared to the control site, which could not be linked to any microbial data. We conclude that medium term (four years) warming and decreased precipitation strongly affected MB and EEA but not MCS in subalpine grassland soils, and that those shifts cannot be readily linked to the dynamics of soil carbon concentration under climate change.

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Cécillon, Lauric. 2017. Climate change effects on the stability and chemistry of soil organic carbon pools in a subalpine grassland. Biogeochemistry,. 123-139. 10.1007/s10533-016-0291-8 Contact CEH NORA team at noraceh@ceh.ac.ukThe NERC and CEH trademarks and logos ('the Trademarks') are registered trademarks of NERC in the UK and other countries, and may not be used without the prior written consent of the Trademark owner. corresponding to specific turnover rates, in winter and in summer. Soil organic matter fraction 41 chemistry was studied with ultraviolet, 3D fluorescence, and mid-infrared spectroscopies. The 42 most labile SOM fractions showed high intra-annual dynamics (amounts and chemistry) 43 mediated via the seasonal changes of fresh plant debris inputs and confirming their high 44 contribution to the microbial loop. Our climate change manipulation modified the chemical 45 differences between free and intra-aggregate organic matter, suggesting a modification of soil 46 macro-aggregates dynamics. Interestingly, the four-year climate manipulation affected 47 directly the SOM dynamics, with a decrease in organic C bulk soil content, resulting from 48 significant C-losses in the mineral-associated SOM fraction (MAOM), the most stable form of 49 SOM. This SOC decrease was associated with a decrease in clay content, above-and 50 belowground plants biomass, soil microbial biomass and activity. The combination of these 51 climate changes effects on the plant-soil system could have led to increase C-losses from the 52 MAOM fraction through clay-SOM washing out and DOC leaching in this subalpine 53 grassland. 54Keywords: Water extractable organic carbon; Particulate organic matter; Mineral associated 55 organic matter; Infrared spectroscopy; 3D Fluorescence spectroscopy 56 57 3