Ecological Modelling 221 (2010) 2068–2075 Contents lists available at ScienceDirect Ecological Modelling journal homepage: www.elsevier.com/locate/ecolmodel Unveiling human-assisted dispersal mechanisms in invasive alien insects: Integration of spatial stochastic simulation and phenology models L.R. Carrasco a,b,∗ , J.D. Mumford a , A. MacLeod b , T. Harwood c , G. Grabenweger d , A.W. Leach a , J.D. Knight a , R.H.A. Baker b a Centre for Environmental Policy, Imperial College London, Exhibition Road, London SW7 2AZ, UK b The Food and Environment Research Agency, Sand Hutton, York YO41 1LZ, UK c CSIRO Entomology, Clunies Ross St., Black Mountain, Canberra, ACT 2601, Australia d Institute for Plant Health, Austrian Agency for Health and Food Safety, Spargelfeldstraße 191, A-1220, Vienna, Austria article info Article history: Received 14 March 2010 Received in revised form 17 May 2010 Accepted 20 May 2010 Available online 18 June 2010 Keywords: Biological invasions Biosecurity Pest risk analysis Policy analysis Spatial stochastic simulation abstract Capturing the spread of biological invasions in heterogeneous landscapes is a complex modelling task where information on both dispersal and population dynamics needs to be integrated. Spatial stochastic simulation and phenology models have rarely been combined to assist in the study of human-assisted long-distance dispersal events. Here we develop a process-based spatially explicit landscape-extent simulation model that considers the spread and detection of invasive insects. Natural and human-assisted dispersal mechanisms are mod- elled with an individual-based approach using negative exponential and negative power law dispersal kernels and gravity models. The model incorporates a phenology sub-model that uses daily tempera- ture grids for the prediction and timing of the population dynamics in each habitat patch. The model was applied to the study of the invasion by the important maize pest western corn rootworm (WCR) Diabrotica virgifera ssp. virgifera in Europe. We parameterized and validated the model using maximum likelihood and simulation methods from the historical invasion of WCR in Austria. WCR was found to follow stratified dispersal where international transport networks in the Danube basin played a key role in the occurrence of long-distance dispersal events. Detection measures were found to be effective and altitude had a significant effect on limiting the spread of WCR. Spatial stochas- tic simulation combined with phenology models, maximum likelihood methods and predicted versus observed regression showed a high degree of flexibility that captured the salient features of WCR spread in Austria. This modelling approach is useful because it allows to fully exploit and the often limited and heterogeneous information available regarding the population dynamics and dispersal of alien invasive insects. © 2010 Elsevier B.V. All rights reserved. 1. Introduction Harmful non-indigenous species (NIS) lead to the extinction of vulnerable native species and to severe alterations of ecosys- tems and agroecosystems (Hulme, 2006). NIS impacts and their management entail considerable economic costs. For instance, the annual costs of control and yield losses due to the invasive pest western corn rootworm (WCR) (Diabrotica virgifera virgifera) and other related rootworm species in the world have been estimated to greatly exceed $1 billion (Gray et al., 2009). ∗ Corresponding author at: Centre for Environmental Policy, Imperial College Lon- don, Exhibition Road, London SW7 2AZ, UK. Tel.: +44 750 141 6712; fax: +44 20 7594 9334. E-mail addresses: roman.carrasco@imperial.ac.uk, romancarrasco@ymail.com (L.R. Carrasco). Understanding the mechanisms underlying the spread of a cer- tain NIS is of great value for decision-makers to identify the most adequate management strategy. Among dispersal mechanisms, long-distance dispersal events have been shown to be highly influ- ential on the spread velocity of NIS (Neubert and Caswell, 2000). Due to the spatial and temporal magnitude of biological inva- sions, experimental approaches to study long-distance dispersal events at the landscape-scale are unfeasible, rendering modelling and empirical analysis of historical invasions as the most suitable methodologies. A very insightful approach for the study of NIS spreading by human-assisted dispersal when spatial time series of data on the invasion are available is the use of empirical methods to fit spa- tially explicit spread models. These approaches have been used to detect long-distance dispersal mechanisms at the landscape- scale by studying the association of human population density and transport networks with the spatial patterns of observed spread. 0304-3800/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.ecolmodel.2010.05.012