Assessing the ecological impacts of invasive species based on their functional responses and abundances

Abstract

Invasive species management requires allocation of limited resources towards the proactive mitigation of those species that could elicit the highest ecological impacts. However, we lack predictive capacity with respect to the identities and degree of ecological impacts of invasive species. Here, we combine the relative per capita effects and relative field abundances of invader as compared to native species into a new metric, ''Relative Impact Potential'' (RIP), and test whether this metric can reliably predict high impact invaders. This metric tests the impact of invaders relative to the baseline impacts of natives on the broader ecological community. We first derived the functional responses (i.e. per capita effects) of two ecologically damaging invasive fish species in Europe, the Ponto-Caspian round goby (Neogobius melanostomus) and Asian topmouth gudgeon (Pseudorasbora parva), and their native trophic analogues, the bullhead (Cottus gobio; also C. bairdi) and bitterling (Rhodeus amarus), towards several prey species. This establishes the existence and relative strengths of the predator-prey relationships. Then, we derived ecologically comparable field abundance estimates of the invader and native fish from surveys and literature. This establishes the multipliers for the above per capita effects. Despite both predators having known 123Biol Invasions (2017) 19:1653-1665 DOI 10.1007/s10530-017-1378 severe detrimental field impacts, their functional responses alone were of modest predictive power in this regard; however, incorporation of their abundances relative to natives into the RIP metric gave high predictive power. We present invader/native RIP biplots that provide an intuitive visualisation of comparisons among the invasive and native species, reflecting the known broad ecological impacts of the invaders. Thus, we provide a mechanistic understanding of invasive species impacts and a predictive tool for use by practitioners, for example, in risk assessments.

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“…and over a fixed timeframe (e.g. 1 hour) (Laverty et al, 2017). The amount of food consumed in that unit of time according to the initial prey density is then defined as the consumption rate of that individual.…”

“…The asymptote of the curve (i.e. the maximal consumption rate) can be determined from (1/h) (Laverty et al, 2017). Differences in a and h between the invader and native species can then be tested for their statistical significance (Dick et al, , 2017aBarrios-O'Neill et al, 2016;Guo et al, 2017;Laverty et al, 2017).…”

“…the maximal consumption rate) can be determined from (1/h) (Laverty et al, 2017). Differences in a and h between the invader and native species can then be tested for their statistical significance (Dick et al, , 2017aBarrios-O'Neill et al, 2016;Guo et al, 2017;Laverty et al, 2017). This testing can be completed in specific R packages, such as 'Functional responses in R' (Frair; Pritchard, 2014;Pritchard, Paterson, Bovy & Barrios-O'Neill, 2017).…”

“…However, this does not necessarily mean these invaders have negligible trophic impacts via their predation, as these results only provide per capita consumption rates. Thus, Laverty et al (2017) revealed how per capita data might be scaled up to population level impacts. For example, they demonstrated that whilst consumption rates of individual invasive P. parva might be relatively low, their propensity for forming highly abundant populations means that when scaled up to population levels, their relative impact potential (Dick et al, 2017a) is substantially elevated and of high ecological concern.…”

“…For example, they demonstrated that whilst consumption rates of individual invasive P. parva might be relatively low, their propensity for forming highly abundant populations means that when scaled up to population levels, their relative impact potential (Dick et al, 2017a) is substantially elevated and of high ecological concern. Indeed, the development of more nuanced experimental and analytical protocols for comparative functional responses for non-native fishes that are, for example, omnivorous and exploitative competitors, enables increased ecological complexity and realism within predictions, thus providing a more robust and powerful predictive tool (Dick et al, 2017a;Laverty et al, 2017;Penk et al, 2017).…”