Using genomics to guide seed-sourcing at the right taxonomical level for ecological restoration projects: the complex case of Carex bigelowii s.lat. in Norway

There is a growing demand for ecological restoration using suitable seeds following international standards or national legal demands for local seed-sourcing. However, before selecting the appropriate geographic origin of seeds, it is vital to explore taxonomic complexity related to the focal taxa. We used ddRAD-seq to screen genomic diversity within Carex bigelowii s.lat. focussing on Norway. This species complex is considered a candidate for seeding, but presents considerable morphological, ecological, and genetic variation. The genetic structure of 132 individuals of C. bigelowii s.lat., including C. nigra as an outgroup, was explored using ordinations, clustering analyses, and a genetic barrier algorithm. Two highly divergent clusters were evident, supporting the recognition of two taxonomic units ‘C. dacica’ and ‘subsp. bigelowii’. Previously defined seed-sourcing regions for C. bigelowii s.lat. did not consider the known taxonomic complexity, and therefore interpreted the overall genetic structure as seed-sourcing regions, not taxa. We estimated genetic neighbourhood sizes within each taxon to be 100-150 km and 300 km, respectively, indicating species-specific delimitations of local seed-sourcing regions. Frequent hybrids, local genetic distinctiveness, and suggested ecotypes add complexity to the discussed seed-sourcing regions. Our results show how genomic screening of diversity and structure in a species complex can alleviate the taxonomic impediment, inform practical questions and legal requirements related to seed-sourcing, and together with traditional taxonomic work provide necessary information for a sound management of biodiversity.

Methods
Leaf samples from 139 individuals of Carex bigelowii s.lat. collected from 33 sites across its Norwegian distribution and 16 sites outside Norway. Information on collection sites, lat and long, collectors and voucher IDs are all given in Table 1 (uploaded to DRYAD).

Preparation of ddRAD-seq libraries, de novo assembly of loci, variant calling and filtering (including MAF sensitivity analyses) are described in the publication.

Two datasets are uploaded:

dataset_A_all_het0.8_r90_maf0.01.vcf includes all SNPs for ordinations (15,095 SNPs, including linked markers from the same locus)

dataset_B_all_het0.8_r90_maf0.01_single_snp.stru includes only one SNP per locus (5,134 SNPs, approximating unlinked markers)