Adapted from a blog post written by Mary Goddard at Wild Frontier Ecology
Wild Frontier Ecology (WFE) was commissioned to undertake invertebrate surveys as part of the post-construction monitoring of a new wind farm in Northamptonshire.
The aim was to help inform an assessment of the condition of grassland field margins that are managed as part of the Habitat Improvement Plan for the site. The work schedule for monitoring prescribed terrestrial invertebrate sampling in years 1, 3, 6 and 9 following the construction of the wind farm, with surveys taking place in the second and third quarters of each year. WFE chose to use DNA metabarcoding as an efficient way of analysing the diversity of the samples.
The survey strategy developed by WFE involves a combination of simple pitfall traps, swish netting and “CWAC” traps (devised by the University of Reading’s Centre for Wildlife Assessment and Conservation). Five survey locations were identified in order to cover variations in the grassland habitat. At each survey point a single CWAC trap was deployed, with three pitfall traps placed one metre from this in a triangle formation. For more details about the trapping methodology, see the full write-up by WFE.
The killing/preservative fluid used in the traps during the first trap deployment in June was a soapy solution, which was an effective killing fluid but not particularly pleasant to work with. Although there was some concern that the quality of the DNA would be compromised because of this, metabarcoding nevertheless yielded good quality and informative data. In the second sampling effort of the year (September) the fluid was changed to an ethanol solution, which was much easier to work with.
The analysis followed our “invertebrate identification from bulk sample” pipeline, which involves grinding up the entire contents of each trap sample, extracting the DNA from the resulting ‘invertebrate soup’ and then sequencing it. You can learn more about the metabarcoding process here. Each sample produces many thousands of DNA sequences, which are quality filtered and compared against a reference library of UK invertebrate species to assign taxonomy. The reference library is extensive but not exhaustive, so any taxon that did not match a species in the library was conservatively assigned to higher-level taxonomy.
In total, we identified 144 unique taxa from the ten samples. The majority (88%) were identified to species level, with the remainder assigned to genus or family. The difference in the taxonomic composition of samples collected in June and September was clearly apparent, and can be seen in the summary data shown below. Diptera (flies) and Coleoptera (beetles) were the dominant taxa in both sampling months, but Heterobranchia (slugs) and Collembola (springtails) were much more abundant in September compared with June. Our report included summary charts like the one below along with a species-by-sample table in MS Excel format, which can be updated with each new set of samples that are processed and can be used to perform more complex community analyses.
Mary Goddard from Wild Frontier Ecology writes:
“The results produced were well presented and easy to interpret. They will be straightforward to compare with the results of subsequent years of sampling. The summary of results presented at the start of the NatureMetrics report gives a concise synopsis of key findings. The information in the report provided by NatureMetrics is in many ways ideal for a site such as this, where we are not expecting the occurrence of any particularly rare or interesting species (which might require specialist search methods) but are more interested in any changes in species composition and abundance. It will be very interesting to see how results compare in following years, with NatureMetrics results allowing us to easily detect changes in the invertebrate communities of the grassland margins of this wind farm.”
It has been a pleasure to work with Wild Frontier Ecology on this project so far and we look forward to receiving further samples in the coming seasons!