Background
The Convention for Biodiversity is a set of agreements signed by 168 countries around the world. A key strategic goal is to “improve the status of biodiversity by safeguarding ecosystems, species and genetic diversity”. To achieve this, a key preliminary step is monitoring changes in biodiversity in order to develop actions to prevent declines. Substantial monitoring for ecosystems and species is already underway, but efforts to monitor of genetic diversity are very limited. This is despite a target (Aichi target # 13) that “By 2020, the genetic diversity of cultivated plants and farmed and domesticated animals and of wild relatives, including other socio-economically as well as culturally valuable species, is maintained, and strategies have been developed and implemented for minimizing genetic erosion and safeguarding their genetic diversity”. This target cannot be achieved without schemes to monitor the genetic diversity of populations. Whilst there is some reporting on the genetic diversity of farmed and domesticated animals, there are no comparable schemes for wild animals and plants, despite comprising many culturally valuable species.
Butterflies are one such culturally-important group, which are highly salient to societies across the world. As a result, we have a good understanding of the ecology for the majority of species, as well as butterfly populations being well-monitored in many countries. In addition, because butterflies are highly sensitive to environmental change, they make an excellent candidate for developing a genetic monitoring scheme.
Plan:
Each year individual butterflies from populations at sites for which long term population abundance monitoring data are available will be collected and archived. These samples will then be analysed for genetic diversity (e.g. using microsatellite markers or RAD sequencing) to allow the development of indicators of the change in genetic diversity at site, regional and national levels. In combination with population abundance data, a range of additional insights also become possible. For example, we anticipate research projects to develop focusing on:
- Developing indicators of functional connectivity (the ability of species to move across landscapes) to improve targeted conservation management
- Understanding how genetic variability mediates resilience to climate change by a) facilitating adaptation to incremental climatic warming, b) reducing population-level sensitivity to extreme climate events and c) facilitating population recovery from such events
- Understanding patterns of genetic variability at geographic range edges and whether genetic variability enhances the ability of populations to expand at leading fronts and to persist at trailing edges
- Additional analyses on spatial and temporal patterns in butterfly ectoparasites (e.g. mites) and commensals (i.e. the insect microbiome).
Progress:
We are currently piloting the population genetics monitoring scheme on a single widespread species, Maniola jurtina (L.), for which have developed new microsatellite markers. Samples from long term population monitoring sites (i.e. UK Butterfly Monitoring Scheme transect routes) have been collected over four years (2012 to 2015) from 15 sites in central Southern England. The protocol involves collecting 20 individuals from each site and storing these in -20°C freezers before DNA is extracted, purified and amplified using microsatellite primers. From September 2016, A PhD student (Matthew Greenwell), will co-ordinate an expansion of sample collection across more UK sites, as well as sites across Europe.
Interested in being involved?
The BGEMS team is a partnership between the University of Reading and the Centre for Ecology and Hydrology. The team currently consists of Dr. Tom Oliver, Dr. Marc Botham, Dr. John Day, Dr. Melanie Gibbs, Matthew Greenwell and Dr. David Roy. We particularly welcome collaborators to who would be prepared to collect annual samples from long-term population monitoring sites, especially in other countries. We also invite collaboration from research teams who may propose innovative ideas to make use of archived samples. For further information, please email: t.oliver@reading.ac.uk