Data from: Recreational vessel networks reveal potential hot spots for marine pest introduction and spread
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https://datadryad.org/dataset/doi:10.5061/dryad.bcc2fqzm6
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Recreational vessels are an important pathway for spreading marine
non-indigenous species (NIS) around coastal environments globally.
However, most vessels are not tracked, limiting our ability to map their
movements and identify locations at greater risk of NIS introductions.
Using New Zealand as a case study, we quantified spread and risk patterns
of recreational vessel movements, using a web-based survey allowing the
more than 1,800 respondents to map significant trips with over 12,000
visits. These vessel routes were used to build a network model
representing nationwide recreational vessel movements. Two proxies were
used to quantify the risk of introduction of marine NIS: (i) incoming hull
length and (ii) cumulative residency periods at sites. There was
significant variation in the distances travelled, the destinations they
visited, and the duration of their stays. New Zealand’s recreational
boating network contained 317 destinations with over 4,000 unique
connections, concentrated within two distinct areas of the country.
Network-based metrics and risk proxies quantified the relative importance
of domestic locations as incursion or spreading hubs for NIS. This
approach highlighted several areas that pose high relative biosecurity
risk within the national network, but are underrepresented within current
surveillance programmes. Synthesis and applications. Our study
demonstrates how the movement dynamics of recreational vessels can be
quantified at a regional scale to inform proactive management. The
identification of spreading hubs and locations at particular risk of NIS
introductions, enables managers to design risk-based and effective
surveillance and monitoring programmes. Our network-based approach to
determine the biosecurity implications posed by recreational vessels is
transferable to other parts of the world. It enables managers to
understand the distribution of risk within an area of interest (e.g., a
jurisdiction) and develop optimised approaches for mitigating impact.
提供机构:
Dryad
创建时间:
2024-04-04



