Rapid evolution may play an important role in the range expansion of invasive species and modify forecasts of invasion, which are the backbone of land management strategies. However, losses of genetic variation associated with colonization bottlenecks may constrain trait and niche divergence at leading range edges, thereby impacting management decisions that anticipate future range expansion. The spatial and temporal scales over which adaptation contributes to invasion dynamics remain unresolved. We leveraged detailed records of the ~130-year invasion history of the invasive polyploid plant, leafy spurge (Euphorbia virgata), across ~500km in Minnesota, U.S.A. We examined the consequences of range expansion for population genomic diversity, niche breadth, and the evolution of germination behavior. Using genotyping-by-sequencing, we found some population structure in the range core, where introduction occurred, but panmixia among all other populations. Range expansion was accompanied by only modest losses in sequence diversity, with small, isolated populations at the leading edge harboring similar levels of diversity to those in the range core. The climatic niche expanded during most of the range expansion, and the niche of the range core was largely non-overlapping with the invasion front. Ecological niche models indicated that mean temperature of the warmest quarter was the strongest determinant of habitat suitability and that populations at the leading edge had the lowest habitat suitability. Guided by these findings, we tested for rapid evolution in germination behavior over the time course of range expansion using a common garden experiment and temperature manipulations. Germination behavior diverged from early to late phases of the invasion, with populations from later phases having higher dormancy at lower temperatures. Our results suggest that trait evolution may have contributed to niche expansion during invasion and that distribution models, which inform future management planning, may underestimate invasion potential without accounting for evolution.

Sampling and sequencing

In 2019, we collected leaf tissue from six individuals in each of 14 populations distributed evenly across Minnesota (hereafter: population samples). In addition, we collected tissue from one individual in each of 157 populations distributed relatively evenly across Minnesota, eastern South Dakota, eastern North Dakota, and western Wisconsin (hereafter: landscape samples). We sampled tissue from individuals that were at least five meters apart to minimize collecting from the same genet and placed tissues immediately in silica for preservation until DNA extraction.

We extracted DNA using QIAGEN DNeasy Plant Mini Kits (QIAGEN Inc.). Dual-indexed GBS (genotyping-by-sequencing) libraries were created using the BamHI + NsiI enzyme combination. All libraries were pooled and sequenced on an Illumina NovaSeq System (Illumina Inc., San Diego, CA, USA) with 1x100-bp sequencing. Once sequenced, the reads were demultiplexed and balanced with a mean quality score ≥ Q30 for all libraries. We filtered low-quality bases using Trimmomatic (Bolger et al. 2014) and used Stacks v.2.5.9 (Rochette et al. 2019) to build loci de novo (i.e., without aligning reads to a reference genome). Overall, we obtained 510 million reads across the 241 samples (599,386 – 3,376,078 of raw reads per individual). Mean read depth per locus ranged from 14x to 26x.

FASTQ format is a text-based format for storing both a biological sequence (usually nucleotide sequence) and its corresponding quality scores. FASTQ files may be opened with any standard text-based file editor (e.g., Notepad).