changing fashions and management interventions) interact to shape these patterns
and determine not only how the pathways of introduction change over time (Hulme
et al. 2008; Essl et al. 2011, 2015; Ojaveer et al. 2017; Saul et al. 2017; Seebens et al.
2017; Zieritz et al. 2017), but also the likelihood that the introduced taxa will become
invasive and have negative impacts in their new range (Cassey et al. 2004; Lambdon
et al. 2008; Lockwood et al. 2009; Wilson et al. 2009; Pyšek et al. 2011; Essl et al.
2015).
Such variations, along with the vast number of potential pathways and economic
globalisation have made it difficult to implement pathway-centred legislation and
prevention strategies. To overcome these obstacles, efforts have been made to
classify or aggregate pathways into categories and in so doing facilitate assessments
of their relative importance (Hulme et al. 2008; Essl et al. 2015). Various classifications have been developed (see Hulme et al. 2008; Wilson et al. 2009) and used in
assessments (e.g. Pyšek et al. 2011; Measey et al. 2017), with one of these,
developed by Hulme et al. (2008), being modified to form the hierarchical pathway
classification scheme that has been adopted by the CBD (CBD 2014). This scheme
classifies pathways, based on their attributes (e.g. degree of human assistance, means
of transport and subsequent introduction), into six main pathway categories (see
Table 12.1 for explanations and examples of the categories) and 44 subcategories
(Fig. 12.1). The detail required for pathway management depends on the management goal (Essl et al. 2015), and the information provided by the hierarchical scheme
can inform management at a number of levels. The six main categories provide
sufficient detail to develop overarching legislation [and also facilitate analyses that
compare trends across regions, taxonomic groups and environments (Hulme et al.
2008)], while the high level of detail provided by the subcategories allows for
decision makers to be better informed, and for tailored regulations and interventions
to be developed and implemented (Essl et al. 2015; Saul et al. 2017).
As biological invasions have major impacts in South Africa (van Wilgen et al.
2001), information on the country’s pathways of introduction is required not only to
meet Aichi Biodiversity Target 9, but also to inform strategies that aim to prevent
invasions by managing introduction pathways. A dataset containing historical introduction data for South Africa was collated during an assessment of South African
alien species databases (Faulkner et al. 2015). The dataset includes information, for
taxa introduced to South Africa, on taxonomy, and date and pathway of introduction,
with the pathway of introduction data classified using the scheme developed by
Hulme et al. (2008) (see Faulkner et al. 2015, 2016 for details on the methodology
followed). The dataset has been used in previous published assessments of
South Africa’s pathways of introduction (see Faulkner et al. 2016), but has been
subsequently updated (see van Wilgen and Wilson 2018) using the pathway classification scheme adopted by the CBD. This update was necessary to assess the status
of South Africa’s pathways of introduction using recently developed indicators for
national level assessments of biological invasions (Wilson et al. 2018). The indicators, however, not only consider the role the pathways play in introducing alien taxa,
but also their prominence or socio-economic importance. Therefore, in order to
populate the indicators for South Africa, socio-economic data and socio-economic
forecasts for the pathways were also obtained from a variety of sources (see van
316
K. T. Faulkner et al.
and determine not only how the pathways of introduction change over time (Hulme
et al. 2008; Essl et al. 2011, 2015; Ojaveer et al. 2017; Saul et al. 2017; Seebens et al.
2017; Zieritz et al. 2017), but also the likelihood that the introduced taxa will become
invasive and have negative impacts in their new range (Cassey et al. 2004; Lambdon
et al. 2008; Lockwood et al. 2009; Wilson et al. 2009; Pyšek et al. 2011; Essl et al.
2015).
Such variations, along with the vast number of potential pathways and economic
globalisation have made it difficult to implement pathway-centred legislation and
prevention strategies. To overcome these obstacles, efforts have been made to
classify or aggregate pathways into categories and in so doing facilitate assessments
of their relative importance (Hulme et al. 2008; Essl et al. 2015). Various classifications have been developed (see Hulme et al. 2008; Wilson et al. 2009) and used in
assessments (e.g. Pyšek et al. 2011; Measey et al. 2017), with one of these,
developed by Hulme et al. (2008), being modified to form the hierarchical pathway
classification scheme that has been adopted by the CBD (CBD 2014). This scheme
classifies pathways, based on their attributes (e.g. degree of human assistance, means
of transport and subsequent introduction), into six main pathway categories (see
Table 12.1 for explanations and examples of the categories) and 44 subcategories
(Fig. 12.1). The detail required for pathway management depends on the management goal (Essl et al. 2015), and the information provided by the hierarchical scheme
can inform management at a number of levels. The six main categories provide
sufficient detail to develop overarching legislation [and also facilitate analyses that
compare trends across regions, taxonomic groups and environments (Hulme et al.
2008)], while the high level of detail provided by the subcategories allows for
decision makers to be better informed, and for tailored regulations and interventions
to be developed and implemented (Essl et al. 2015; Saul et al. 2017).
As biological invasions have major impacts in South Africa (van Wilgen et al.
2001), information on the country’s pathways of introduction is required not only to
meet Aichi Biodiversity Target 9, but also to inform strategies that aim to prevent
invasions by managing introduction pathways. A dataset containing historical introduction data for South Africa was collated during an assessment of South African
alien species databases (Faulkner et al. 2015). The dataset includes information, for
taxa introduced to South Africa, on taxonomy, and date and pathway of introduction,
with the pathway of introduction data classified using the scheme developed by
Hulme et al. (2008) (see Faulkner et al. 2015, 2016 for details on the methodology
followed). The dataset has been used in previous published assessments of
South Africa’s pathways of introduction (see Faulkner et al. 2016), but has been
subsequently updated (see van Wilgen and Wilson 2018) using the pathway classification scheme adopted by the CBD. This update was necessary to assess the status
of South Africa’s pathways of introduction using recently developed indicators for
national level assessments of biological invasions (Wilson et al. 2018). The indicators, however, not only consider the role the pathways play in introducing alien taxa,
but also their prominence or socio-economic importance. Therefore, in order to
populate the indicators for South Africa, socio-economic data and socio-economic
forecasts for the pathways were also obtained from a variety of sources (see van
316
K. T. Faulkner et al.