(Higgins et al. 1999; Robertson et al. 2001; Rouget et al. 2004; Trethowan et al.
2011; Walker et al. 2017), and a wide range of other taxa including alien amphibians
(Davies et al. 2019), crayfish (Nunes et al. 2017), fish (Lubcker et al. 2014; Zengeya
et al. 2013), and fruit flies (De Meyer et al. 2010). Such models have also been used
to predict future potential invaders, e.g. to assist in the development of a watch list of
species (Faulkner et al. 2014), and to inform surveillance efforts (Faulkner et al.
2017).
Importantly, however, the broad-scale environmental variables typically used as
input to species distribution models permit only broad-scale predictions. Humanmediated changes, for instance to water stress (e.g. through irrigation) are difficult to
capture in such models. There has been more success in integrating the role of
human-caused disturbances by using integrative variables like the “human footprint”
(“Global Human Influence Index”) metric or other proxies of human influence such
as road density or human population density (e.g. Donaldson et al. 2014; Richardson
et al. 2005; Thuiller et al. 2006).
To date, most of the distribution modelling has relied on correlative approaches
but an increasing use of mechanistic models is likely to both improve the predictions
and help identify testable hypotheses that can provide insights for management
(Kearney and Porter 2009). Studies have also investigated issues associated with
predicting potential distributions, in some cases highlighting important invasion
dynamics (Le Maitre et al. 2008; Wilson et al. 2007). For example, the distribution
of Port Jackson Willow (Acacia saligna) in South Africa does not match its climatic
envelope in Western Australia due to introductions originating from an admixed
novel genetic entity (Thompson et al. 2011). Understanding sub-specific variation in
potential distributions is increasingly recognised as an important consideration in
species distributions modelling for invasions (Smith et al. 2019).
13.5 Extreme Climatic Events and Large Infrequent
Disturbances
Extreme climatic events (Easterling et al. 2000) and large infrequent disturbances
(Turner and Dale 1998) can have profound and long-lasting impacts on the function
of ecosystems (Parsons et al. 2006), including on where alien species establish,
spread, and invade. Globally, disturbances such as floods and droughts are predicted
to increase in severity and frequency due to the effects of global climate change
(Lesnikowski et al. 2015). In South Africa, while there is considerable variability in
precipitation spatially and temporally (Rouault and Richard 2003), this inter-annual
variability has increased over the last ~50 years (Fauchereau et al. 2003). Droughts
are likely to become more intense and widespread, and trends show the probability
of extreme rainfall increasing (van Wilgen et al. 2020b, Chap. 29). Such changes in
climatic conditions are expected to influence invasions (Chown 2010), although the
implications and mechanisms are not well understood (Diez et al. 2012).
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J. R. Wilson et al.
2011; Walker et al. 2017), and a wide range of other taxa including alien amphibians
(Davies et al. 2019), crayfish (Nunes et al. 2017), fish (Lubcker et al. 2014; Zengeya
et al. 2013), and fruit flies (De Meyer et al. 2010). Such models have also been used
to predict future potential invaders, e.g. to assist in the development of a watch list of
species (Faulkner et al. 2014), and to inform surveillance efforts (Faulkner et al.
2017).
Importantly, however, the broad-scale environmental variables typically used as
input to species distribution models permit only broad-scale predictions. Humanmediated changes, for instance to water stress (e.g. through irrigation) are difficult to
capture in such models. There has been more success in integrating the role of
human-caused disturbances by using integrative variables like the “human footprint”
(“Global Human Influence Index”) metric or other proxies of human influence such
as road density or human population density (e.g. Donaldson et al. 2014; Richardson
et al. 2005; Thuiller et al. 2006).
To date, most of the distribution modelling has relied on correlative approaches
but an increasing use of mechanistic models is likely to both improve the predictions
and help identify testable hypotheses that can provide insights for management
(Kearney and Porter 2009). Studies have also investigated issues associated with
predicting potential distributions, in some cases highlighting important invasion
dynamics (Le Maitre et al. 2008; Wilson et al. 2007). For example, the distribution
of Port Jackson Willow (Acacia saligna) in South Africa does not match its climatic
envelope in Western Australia due to introductions originating from an admixed
novel genetic entity (Thompson et al. 2011). Understanding sub-specific variation in
potential distributions is increasingly recognised as an important consideration in
species distributions modelling for invasions (Smith et al. 2019).
13.5 Extreme Climatic Events and Large Infrequent
Disturbances
Extreme climatic events (Easterling et al. 2000) and large infrequent disturbances
(Turner and Dale 1998) can have profound and long-lasting impacts on the function
of ecosystems (Parsons et al. 2006), including on where alien species establish,
spread, and invade. Globally, disturbances such as floods and droughts are predicted
to increase in severity and frequency due to the effects of global climate change
(Lesnikowski et al. 2015). In South Africa, while there is considerable variability in
precipitation spatially and temporally (Rouault and Richard 2003), this inter-annual
variability has increased over the last ~50 years (Fauchereau et al. 2003). Droughts
are likely to become more intense and widespread, and trends show the probability
of extreme rainfall increasing (van Wilgen et al. 2020b, Chap. 29). Such changes in
climatic conditions are expected to influence invasions (Chown 2010), although the
implications and mechanisms are not well understood (Diez et al. 2012).
368
J. R. Wilson et al.