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ECOGEN - Ecosystem change and species persistence over time: a genome-based approach Main goal Develop high taxonomic resolution ancient environmental DNA methods in order to evaluate how drivers of change (human, climate, biota) affect species persistence and ecosystem tipping points in arctic-alpine biomes Subgoals 1) Improve methods for full genome analyses of environmental DNA 2) Compile palaeo data to plan a balanced design of climatic and human impacts 3) Do full genome analyses of lake cores to obtain information on past presence and abundance of vascular plant species and key herbivores 4) Identify biotic drivers and disentangle their effects from human land use and climate change on ecosystem resilience and ecosystem services 5) Estimate species persistence across periods of changes and identify factors causing extinction 6) Provide methods and knowledge to inform species conservation and ecosystem management Summary – see announcement Project tasks We are seeking a research fellow that will join a cross-disciplinary team (ecology, palaeoecology, genetics, archaeology, geology, niche modelling) working in two geographical regions (Norway and the Alps). We will expand our knowledge on past vascular plant and animal diversity and abundance at a taxonomic depth that has not been possible until now due to methodological limitations. We expect to disentangle the effects of past human land-use (hunting, husbandry, burning, agriculture), climate change, and biota on species and ecosystem changes and thereby be able to answer questions central to our understanding of our biological resources, such as the level of persistence of species and resilience of ecosystems to environmental drivers, the extinction risk of species, and the capacity of mountain landscape to buffer against these changes. By identifying drivers of shifts in ecosystem services through time, we may inform future management. The successful candidate will work on development of improved technology. The most recent applications of ancient plant DNA analyses are largely developed by our team (Taberlet et al. 2007, Sønstebø et al. 2010, Yoccoz et al. 2012, Willerslev et al. 2014). For vascular plants, the 50-100 base pair long P6 loop region of the chloroplast trnL (UAA) intron is used in a PCR based method (Taberlet et al. 2007), which allows identification of all plant families, most genera (>75%), and one third of the species (Sønstebø et al. 2010). When applied to modern lake sediments, half of the species present within 2 m of lakes were detected (Alsos et al. In prep.). Our recent study of an 8500 year old core from Svalbard show that the method detect all except two genera identified in a macrofossil study from the same lake (Alsos et al. 2015). Overall, 1.2 times more taxa of vascular plants were identified with ancient DNA than macrofossils, and the number of taxa identified per sample was 2.7 times higher for the former. Thus, DNA analyses of Holocene lake sediment can reveal the presence of rare taxa and thereby allow for a better estimation of species persistence (Fig. 1). Further, the method is now resource-efficient and repeatable, and it can be extended to any group of organisms, given that a DNA reference library and adequate primers are developed . It also allows for semi-quantitative interpretations based on the number of PCR repeats where taxa are identified (Pansu et al. 2015). We will do minor optimization of these applications and analyse all samples for vascular plants and key herbivores. 1 Arabis alpinazones seeds Macrofossil Saliceae sedaDNA Arabis alpina sedaDNA Lithostratigraphic units 1 4 2 M3 L5 M2 L4 L3 M1 L2 L1 4 25 2 Ranunculaceae Dryas leaves Taxon richness sedaDNA20 0 15 sedaDNA Age (cal. BP) 10 4 Salix reticulata Taxon richnessleaves Dryas sedaDNA 2000 3000 4000 5000 6000 7000 8000 5 1000 0 macrofossils 0 12 Sedimentary aDNA zones 4 40 D3 D2 D1 Salix polaris leavessedaDNA Koeniga islandica LOI (% dry weight) 8 Macrofossil zones M3 M2 M1 0 Arabis alpina seeds Lithostratigraphic units 41 4 L5 L4 L3 L2 L1 2 Saliceae sedaDNA 25 Arabis alpina sedaDNA 0.2 20 XRF K richness / sum Taxon 4 0.1 sedaDNA 2 Dryas leaves sedaDNA15 Ranunculaceae 10 0 60 Taxon richness 5 Sand and coarse silt 4 4 40 macrofossils 0 volume)leaves Salix(% reticulata Dryas sedaDNA 4 20 0 Koeniga islandica sedaDNA 12 40 Salix polaris leaves 100 150 200 250 300 350 400 450 500 550 1 LOI (%alpina dry weight) 8 50 Arabis seeds 0 2 Depth (cm below sediment surface) Arabis alpina sedaDNA 44 Fig. 2. TaxasedaDNA detected by macrofossil (numbers of fragments) and ancient sedimentary DNA (number of PCR repeats where taxa were Saliceae 0.2 4 discovered). Koenigia islandica was only detected by sediment ancient DNA (sedaDNA), whereas Arabis alpina and Dryas XRF K / sum Ranunculaceae sedaDNA 0.1 frequent in sedaDNA. Note that while macrofossil indicate scattered occurrence of species through octopetala, were detected more 2 Dryasancient leaves time, DNA shows more 60 4 clearly that they actually did persist (Alsos et al. 2015 ). 0 Salix leaves Sand reticulata and coarse silt 4 40 0the P6 loop do however limit the taxonomic information. In addition, as The short fragments of volume) Dryas(% sedaDNA many sequence errors20 generally are produced during PCR, it is necessary to use very stringent 40 Salix polaris leaves 12 filtering conditions reducing the amount of usable data (Coissac et al. 2012). To overcome these 0 50 100 150 200 250 300 350 400 450 500 550 problems, we will do shotgun sequencing of the DNA extracts from lake sediments and thus LOI (% dry weight) 48 Depth (cm sediment biases surface)(Jónsson et al. 2013), the avoiding specific PCR.4 After being corrected forbelow deamination Saliceae sedaDNA resulting sequences will be mapped against the new taxonomic reference library composed of whole 0.2 2 plastid and nuclear ribosomal DNA (see details in Taberlet et al. 2012). A whole genome XRF Kleaves / genomes sum Dryas 0.1 0 reference library is currently being built using a shotgun approach for the alpine flora of the Alps 4 60 (PhyloAlps, 1500 species) and Norway (NorBOL, 2000 species http://www.norbol.org/). The new Dryas sedaDNA Sand and coarse silt reference libraries will40give low coverage for single copy nuclear genes but sufficient coverage for (% volume) 12 are present in many copies per cell. The new genomic reference library plastid and rDNA which 20 will thus include the LOI (% dryalso weight) 8 classic barcoding markers (CBOL et al. 2009) and the P6 loop. Thus, 50 in 100 150attempt 200 of 250 300 analyses 350 400 450 500 550 samples so while identification of 4taxa the only shotgun of ancient sediment far was strongly limited by data available in reference librariessurface) (Smith et al. 2015), our complete Depth (cm below sediment 0.2 reference libraries may allow 100% resolution at species level for vascular plants and key XRF K / sum 0.1 our new shotgun applications will also improve the quantitative herbivores. In addition, 60 interpretation of past flora and fauna as it avoids the PCR step. Sand and coarse silt (% volume) 40 References 20 Alsos I.G., Sjögren P., Edwards M.E., et al. (2015). Sedimentary ancient DNA from Lake Skartjørna, Svalbard: Assessing the resilience of arctic flora50to Holocene 100 climate 150 change. 200 The 250Holocene. 300 10.1177/0959683615612563. 350 400 450 500 550 CBOL PWG, Hollingsworth PM, Forrest LL, et al. 2009. A DNA barcode for land plants. Proceedings of the National Academy of Depth (cm below sediment surface) Sciences 106: 12794-12797. Coissac E, Riaz T, Puillandre N. 2012. Bioinformatic challenges for DNA metabarcoding of plants and animals. Molecular Ecology 21: 1834-1847. Jonsson H, Ginolhac A, Schubert M et al. 2013. mapDamage2. 0: fast approximate Bayesian estimates of ancient DNA damage parameters. Bioinformatics btt193. Pansu J, Giguet-Covex C, Ficetola GF, et al. 2015. Reconstructing long-term human impacts on plant communities: an ecological approach based on lake sediment DNA. Molecular Ecology 24: 1485-1498. Smith O, Momber G, Bates R, et al. 2015. Sedimentary DNA from a submerged site reveals wheat in the British Isles 8000 years ago. Science 347: 998-1001. Sønstebø JH, Gielly L, Brysting AK, et al. 2010. Using next-generation sequencing for molecular reconstruction of past Arctic vegetation and climate. Molecular Ecology Resources 10: 1009-1018. Taberlet P, Coissac E, Pompanon F, et al. 2007. Power and limitations of the chloroplast trnL (UAA) intron for plant DNA barcoding. Nucleic Acids Research 35: e14. Willerslev E, Davison J, Moora M, et al. 2014. Fifty thousand years of Arctic vegetation and megafaunal diet. Nature 506: 47-51. Yoccoz NG, Bråthen KA, Gielly L, et al. 2012. DNA from soil mirrors plant taxonomic and growth form diversity. Molecular Ecology 21: 3647-3655. 2