Modelling the likelihood of entry of marine non-indigenous species from internationally arriving vessels to maritime ports: a case study using New Zealand data

Abstract

The establishment of marine non-indigenous species (NIS) in new locations can degrade environmental, socio-cultural, and economic values. Vessels arriving from international waters are the main pathway for the entry of marine NIS, via exposure due to ballast water discharge (hereafter, ballast discharge) and biofouling. We developed a systematic statistical likelihood-based methodology to investigate port-level marine NIS propagule pressure from ballast discharge and biofouling exposure using a combination of techniques, namely k-Nearest-Neighbour and random forest algorithms. Vessel characteristics and travel patterns were assessed as candidate predictors. For the ballast discharge analysis, the predictors used for model building were vessel type, dead weight tonnage, and the port of first arrival; the predictors used for the biofouling analysis were days since last antifouling paint, mean vessel speed, dead weight tonnage, and hull niche area. Propagule pressure for both pathways was calculated at a voyage, port and annual level, which were used to establish the relative entry score for each port. The model was applied to a case study for New Zealand. Biosecurity New Zealand has commissioned targeted marine surveillance at selected ports since 2002 to enable early detection of newly arrived marine NIS (Marine High-Risk Site Surveillance, MHRSS). The reported methodology was used to compare contemporary entry likelihoods between New Zealand ports. The results suggested that Tauranga now receives the highest volume of discharged ballast water and has the second most biofouling exposure compared to all other New Zealand ports. Auckland was predicted to receive the highest biofouling mass and was ranked tenth for ballast discharge exposure. Lyttelton, Napier, and New Plymouth also had a high relative ranking for these two pathways. The outputs from this study will inform the refinement of the MHRSS programme, facilitating continued early detection and cost-effective management to support New Zealand’s wider marine biosecurity system. More generally, this paper develops an approach for using statistical models to estimate relative likelihoods of entry of marine NIS.