Assessing marine biosecurity risks when data are limited: bioregion pathway and species-based exposure analyses

ICES Journal of Marine Science ICES Journal of Marine Science (2015), 72(3), 1078– 1091. doi:10.1093/icesjms/fsu236 Contribution to the Themed Section: ‘Risk Assessment’ Original Article Assessing marine biosecurity risks when data are limited: bioregion pathway and species-based exposure analyses 1 National Centre for Marine Conservation and Resource Sustainability, University of Tasmania, Locked Bag 1370, Newnham, Tasmania 7250, Australia School of Science, Faculty of Science and Engineering, University of Waikato, Private Bag 3105, Hamilton 3240, New Zealand 3 Environmental Research Institute, Faculty of Science and Engineering, University of Waikato, Private Bag 3105, Hamilton 3240, New Zealand 2 *Corresponding author: tel: +64 27 456 3930; fax: +64 7 838 4218; e-mail: Azmi, F., Primo, C., Hewitt, C. L., and Campbell, M. L. Assessing marine biosecurity risks when data are limited: bioregion pathway and species-based exposure analyses. – ICES Journal of Marine Science, 72: 1078 – 1091. Received 1 April 2014; revised 24 November 2014; accepted 3 December 2014; advance access publication 23 December 2014. We evaluated two risk models (bioregion pathway and species-based exposure), with the aim to determine an effective strategy to implement marine biosecurity risk management in regions/countries where biological data are limited. We used the Port of Tanjung Priok, Jakarta Bay, Indonesia, as a case study to test both models. The bioregion pathway model illustrates that Tanjung Priok is highly connected to the East Asian Sea (91%), and the Northwest Pacific, Mediterranean, and Australia & New Zealand bioregions (“Very Low” risk), with other bioregions posing “Negligible” risk, highlighting the importance of understanding regional port linkages. The bioregion pathway model strength is grounded by using readily available shipping data; however, it does not classify species into threat categories but considers a larger number of species as an increasing threat. The species exposure model found that 51 species pose a theoretical risk (10 “Moderate”, 20 “High”, and 21 “Extreme” risks) to Tanjung Priok. These 51 species can be used as a “watch list” for this port. If biosecurity measures for this port were restricted to the outcomes of the bioregion pathway model only 4 of the 51 species highlighted by the species exposure model would have been captured. The species model was data intensive, requiring extensive species datasets and consequently may be unsuitable when data are limited. Keywords: ballast water, biofouling, biological invasions, developing countries, Indonesia, risk management. Introduction Effective management of non-indigenous marine and estuarine species (hereafter NIMES) relies on data about place (pathway epidemiology on local, regional, and international scales), vector (what are the likely transfer mechanisms, exposure, and vector strength), and species (what species are already present in the waters of concern, what species are present along the vector pathways). These data often inform risk assessment processes to enhance capabilities to protect a country’s external (Hayes and Sliwa, 2003; Hewitt et al., 2004, 2009a, 2011; Floerl et al., 2005; Campbell, 2011; Ruiz et al., 2011) and internal borders (Wyatt et al., 2005; Campbell, 2008; Herborg et al., 2008; Therriault and Herborg, 2008; Hulme, 2009; Campbell and Hewitt, 2011). However, these types of data are often lacking in an aquatic ecosystem context, especially for developing economies and economies in transition (e.g. Raaymakers and Hilliard, 2002; Endresen et al., 2004; International Maritime Organisation GloBallast Partnership, http://globallast.imo.org/index.asp?page=gef_interw_project. htm&menu=true). Consequently, strategies to implement biosecurity risk assessments that are robust when data are deficient are critically needed (e.g. Barry et al., 2008; Dahlstrom et al., 2011). To evaluate the biosecurity implications of the absence of biological data, we focused on the Coral Triangle Initiative (CTI) region (encompassing the Philippines, parts of Malaysia, Indonesia, Timor Leste, parts of Papua New Guinea, and the Solomon Islands; http://www.coraltriangleinitiative.org/, accessed 16 December 2014), in particular the port of Tanjung Priok. Tanjung Priok is the largest and busiest port in Indonesia (Nur et al., 2001), sitting with Jakarta Bay and bordered by the Thousand Islands archipelago and the coastal megacity of Jakarta, which suffers from a high level of pollution (Nicholls, 1995; # International Council for the Exploration of the Sea 2014. All rights reserved. For Permissions, please email: Fauziah Azmi1, Carmen Primo 1, Chad L. Hewitt 1,2, and Marnie L. Campbell 1,3* 1079 Assessing marine biosecurity risks when data are limited Methods Model assumptions A number of assumptions was made to manage the levels of uncertainty associated with data availability and to meet desired quarantine or impact outcomes. (i) These risk assessments identify the vessel as the vector and do not differentiate between biofouling and ballast water. As a consequence, factors that potentially affect transfer survival (e.g. vessel speed, transit time, time in source port) are not considered here, as these tend to influence the numbers of individuals, but not the presence of NIMES associated with a vessel (Gollasch, 2002; Minchin and Gollasch, 2002; Hewitt et al., 2009a, b, 2011). (ii) All species are assumed to survive in the Port of Tanjung Priok. Environmental factors, such as temperature and salinity, are typically used to generate an “environmental matching” in risk assessments. These have been excluded in the bioregion pathway analysis and risk characterization process because they do not portray the likelihood of arrival, but influence establishment (see also discussion in Hewitt and Hayes, 2002; Leppäkoski and Gollasch, 2006; Barry et al., 2008; Hewitt et al., 2009a, 2011). (iii) As previously stated, if there is a record of an NIMES occurrence in a location within a bioregion, then the species is assumed to occur throughout that bioregion (Hewitt et al., 2009a, 2011). (iv) Jakarta Bay occurs in the “East Asian Seas” bioregion (Bioregion 13; Figure 1), which is excluded from the bioregion pathway analysis based on assumption 3. Hence, any species in Bioregion 13 is considered to be present in Jakarta Bay. If published data were available at a finer resolution then this assumption could be modified to represent a finer resolution. We have not undertaken a sensitivity analysis to justify the resolution because the data availability is very patchy. Thus, the bioregion pathway analysis only assesses pathways from the other 17 bioregions. (v) In the bioregion-based pathway analysis: (a) all NIMES were considered to pose the same level of threat; no distinction was made between NIMES because the aim is to evaluate which bioregions would be more likely to be donors of NIMES (regardless of pot (...truncated)