DOI: 10.5061/dryad.g4f4qrfvx
title: Incorporation of colonization pressure into the propagule pressure-based global ballast water standard

description: In 2024 cargo vessels must meet the International Maritime Organization’s
 global ballast water discharge standards (IMO D-2) that limit the
 concentration of living organisms. D-2 focuses on reducing invasion risk
 by reducing ‘community propagule pressure (CPP)’, though it does not
 consider colonization pressure (CP). We modeled risk differences in IMO
 D-2-compliant discharges (10 ind. m-3) for communities that had inverse
 patterns of CP and species’ individual propagule pressures (IPP).
 Secondly, we determined the effect on risk of varying CPP and CP. As part
 of this we tested whether the IMO D-2 standard for zooplankton-sized
 organisms of &lt;10 individuals m-3 was an optimal choice. Risk was
 defined as probability of at least one species invading using four
 risk-release models. Risk differed strongly at the D-2 limit based on
 community composition. At low CPP (&lt;25 ind. m-3), risk was strongly
 affected by CP for hyperbolic and linear risk-release models and weakly
 for exponential and logistic models, while CPP affected only the former
 two model types. Across a much wider range of CPP values, risk was
 affected by CP, CPP, and by their interaction for all models. The IMO D-2
 standard for zooplankton-sized organisms requires very low CPP and even
 lower IPPs in mixed-species releases, which will impede successful
 colonization. Species-abundance theory predicts that discharges meeting
 the D-2 standard (low CPP) will also have low CP. Much more empirical data
 is required to determine whether vessels can consistently reduce CP as it
 lower CPP in order to meet these requirements.
description: Data was collected through a mechanistic model. The model
 considered real-world Ballast water volumes from Bradie, Rolla, Bailey
 & MacIsaac (2022), which consisted of 10000 recorded ballast water
 discharges that ranged from 20 to 1060620 m3 (13871 ± 25738, mean ±
 standard deviation). Using these volumes we then set community propagule
 pressure and colonization pressure while varying individual propagule
 pressure to determine the risk of the establishment (1 - risk of
 extinction). Next, we set individual propagule pressure, colonization
 pressure, and community propagule pressure and determined the risk of
 establishment. Each combination of community propagule pressure,
 individual propagule pressure, and colonization pressure was run for 100
 iterations to simulate 100 trips.  The risk of
 establishments per species across 100 trips was used to calculate the
 probability of at least one species establishing following Wonham, Byers,
 Grosholz & Leung (2013). Additionally, the probability of exactly
 one species establishing by comparing the establishment probability per
 species to a uniform distribution. This comparison determined if a single
 species established or became extinct in a single trip. From the
 establishment or extinct classifications, we determined how many species
 established on a single trip. We then calculated the probability of
 ‘exactly one species establishing’ by dividing the number of trips in
 which exactly one species established by the total number of trips per
 community propagule pressure and colonization pressure. Lastly, we fit the
 risk-release relationship by linear, hyperbolic (Michaelis-Menten),
 exponential, and logistic. For more details, please see
 the corresponding paper. Bradie, J. N., Rolla, M.,
 Bailey, S. A., MacIsaac, H. J. (2022). Managing risk of non-indigenous
 species establishment associated with ballast water discharges from ships
 with inoperable or bypassed ballast water management systems. Journal of
 Applied Ecology, 60, 193-204. doi.org/10.1111/1365-2664.1432
 Wonham, M. J., Byers, J. E., Grosholz, E. D., Leung, B. (2013).
 Modeling the relationship between propagule pressure and invasion risk to
 inform policy and management. Ecological Applications, 23, 1691-1706.
 doi.org/10.1890/12-1985.1
description: All data files are provided in comma-separated value (.csv)
 format. Owing to the large file size, we recommend files be opened in
 statistical software (e.g. R, Python).