Using soil seed banks to assess temporal patterns of genetic variation in invasive plant populations.

Most research on the genetics of invasive plant species has focused on analyzing spatial differences among existing populations. Using a long-established Gunnera tinctoria population from Ireland, we evaluated the potential of using plants derived from seeds associated with different soil layers to track genetic variation through time. This species and site were chosen because (1) G. tinctoria produces a large and persistent seed bank; (2) it has been present in this locality, Sraheens, for ∼90 years; (3) the soil is largely undisturbed; and (4) the soil's age can be reliably determined radiometrically at different depths. Amplified fragment length polymorphic markers (AFLPs) were used to assess differences in the genetic structure of 75 individuals sampled from both the standing population and from four soil layers, which spanned 18 cm (estimated at ∼90 years based on (210)Pb and (137)Cs dating). While there are difficulties in interpreting such data, including accounting for the effects of selection, seed loss, and seed migration, a clear pattern of lower total allele counts, percentage polymorphic loci, and genetic diversity was observed in deeper soils. The greatest percentage increase in the measured genetic variables occurred prior to the shift from the lag to the exponential range expansion phases and may be of adaptive significance. These findings highlight that seed banks in areas with long-established invasive populations can contain valuable genetic information relating to invasion processes and as such, should not be overlooked.

Simulating the effects of climate change on the distribution of an invasive plant, using a high resolution, local scale, mechanistic approach: challenges and insights.

The growing economic and ecological damage associated with biological invasions, which will likely be exacerbated by climate change, necessitates improved projections of invasive spread. Generally, potential changes in species distribution are investigated using climate envelope models; however, the reliability of such models has been questioned and they are not suitable for use at local scales. At this scale, mechanistic models are more appropriate. This paper discusses some key requirements for mechanistic models and utilises a newly developed model (PSS[gt]) that incorporates the influence of habitat type and related features (e.g., roads and rivers), as well as demographic processes and propagule dispersal dynamics, to model climate induced changes in the distribution of an invasive plant (Gunnera tinctoria) at a local scale. A new methodology is introduced, dynamic baseline benchmarking, which distinguishes climate-induced alterations in species distributions from other potential drivers of change. Using this approach, it was concluded that climate change, based on IPCC and C4i projections, has the potential to increase the spread-rate and intensity of G. tinctoria invasions. Increases in the number of individuals were primarily due to intensification of invasion in areas already invaded or in areas projected to be invaded in the dynamic baseline scenario. Temperature had the largest influence on changes in plant distributions. Water availability also had a large influence and introduced the most uncertainty in the projections. Additionally, due to the difficulties of parameterising models such as this, the process has been streamlined by utilising methods for estimating unknown variables and selecting only essential parameters.