Reconstruction of a windborne insect invasion using a particle dispersal model, historical wind data, and Bayesian analysis of genetic data

Abstract

Understanding how invasive species establish and spread is vital for developing effective management strategies for invaded areas and identifying new areas where the risk of invasion is highest. We investigated the explanatory power of dispersal histories reconstructed based on local-scale wind data and a regional-scale wind-dispersed particle trajectory model for the invasive seed chalcid wasp Megastigmus schimitscheki (Hymenoptera: Torymidae) in France. The explanatory power was tested by: (1) survival analysis of empirical data on M. schimitscheki presence, absence and year of arrival at 52 stands of the wasp's obligate hosts, Cedrus (true cedar trees); and (2) Approximate Bayesian analysis of M. schimitscheki genetic data using a coalescence model. The Bayesian demographic modeling and traditional population genetic analysis suggested that initial invasion across the range was the result of long-distance dispersal from the longest established sites. The survival analyses of the windborne expansion patterns derived from a particle dispersal model indicated that there was an informative correlation between the M. schimitscheki presence/absence data from the annual surveys and the scenarios based on regional-scale wind data. These three very different analyses produced highly congruent results supporting our proposal that wind is the most probable vector for passive long-distance dispersal of this invasive seed wasp. This result confirms that long-distance dispersal from introduction areas is a likely driver of secondary expansion of alien invasive species. Based on our results, management programs for this and other windborne invasive species may consider (1) focusing effort at the longest established sites and (2) monitoring outlying populations remains critically important due to their influence on rates of spread. We also suggest that there is a distinct need for new analysis methods that have the capacity to combine empirical spatiotemporal field data, genetic data, and environmental data to investigate dispersal and invasion.

Keywords: Cedrus; HYSPLIT; Megastigmus; invasion; long-distance dispersal; microsatellite; wind.

Figure 1

The survey sites showing the year of arrival and the CLIMATIK weather stations used in the DIYABC analysis. All sites included in the annual survey (Table S1) are included on this map, but only those sites where Megastigmus schimitscheki specimens were collected for the genetic analysis have name codes associated with them. These study sites are shown as: Ardene (Ar), Barrs (Ba), Castellane (Ca), Gap (Gp), Grand Luberon (Gl), Luberon Crete (Lc), Lure (Lu), Mirabel (Mi), Saou (Su), Saumon (Sa), Sisteron (Si), Venasque (Vq),Ventoux (Vx), Vesc (Vs). Survey sites where M. schimitscheki has not been detected are shown as “not detected”.

Figure 2

Probability of colonization by Megastigmus schimitscheki estimated based on the number of HYSPLIT wind-dispersed particle trajectory point estimates in each 10 km × 10 km cell across southeastern France. The NOAA- HYSPLIT wind-dispersed particle trajectory model was used to model the travel paths of particles (representing passively dispersed wasps) released from each study site every day in May each year following colonization of each site (for model results for dispersal from a single study site on a single day see Figure S1). Three subsets of this particle trajectory data were overlaid on a grid of 10 km × 10 km cells covering the study area to create the scenarios for the DIYABC and Survival analyses: (1) Long-distance dispersal from Mont Ventoux: only those trajectories originating at Mont Ventoux, the apparent site of M. schimitscheki introduction to France, (2) Short-distance dispersal from all sites: trajectories originating from any colonized study site starting from the year the site was identified as colonized during the annual surveys, and (3) Short-distance dispersal from all sites plus 4-year delay: trajectories originating from any colonized study site starting 4 years after the site was identified as colonized during the annual surveys. For each of these scenarios, the number of particle trajectories which passed over each grid cell was counted and summed from 1 year to the next to create an estimate of the probability of colonization at each study site in each year. This figure shows the sum of particle trajectories passing over each grid cell using the Short-distance dispersal from all sites scenario in years 1995, 2000, 2005, and 2010. The estimated year of colonization for each study site is also shown.

Figure 3

The four scenarios used in the DIYABC analysis. The study sites are shown as: Ardene (Ar), Barres (Ba), Castellane (Ca), Gap (Gp), Grand Luberon (Gl), Luberon Crete (Lc), Lure (Lu), Mirabel (Mi), Saou (Su), Saumon (Sa), Sisteron (Si), Venasque (Vq),Ventoux (Vx), Vesc (Vs).