Modelling the damage costs of invasive alien species

Abstract

The rate of biological invasions is growing unprecedentedly, threatening ecological and socioeconomic systems worldwide. Quantitative understandings of invasion temporal trajectories are essential to discern current and future economic impacts of invaders, and then to inform future management strategies. Here, we examine the temporal trends of cumulative invasion costs by developing and testing a novel mathematical model with a population dynamical approach based on logistic growth. This model characterises temporal cost developments into four curve types (I–IV), each with distinct mathematical and qualitative properties, allowing for the parameterization of maximum cumulative costs, carrying capacities and growth rates. We test our model using damage cost data for eight genera (Rattus, Aedes, Canis, Oryctolagus, Sturnus, Ceratitis, Sus and Lymantria) extracted from the InvaCost database—which is the most up-to-date and comprehensive global compilation of economic cost estimates associated with invasive alien species. We find fundamental differences in the temporal dynamics of damage costs among genera, indicating they depend on invasion duration, species ecology and impacted sectors of economic activity. The fitted cost curves indicate a lack of broadscale support for saturation between invader density and impact, including for Canis, Oryctolagus and Lymantria, whereby costs continue to increase with no sign of saturation. For other taxa, predicted saturations may arise from data availability issues resulting from an underreporting of costs in many invaded regions. Overall, this population dynamical approach can produce cost trajectories for additional existing and emerging species, and can estimate the ecological parameters governing the linkage between population dynamics and cost dynamics.

Managing biological invasions: the cost of inaction

“…If we assume that cumulative economic impact eventually saturates over time, the costs associated with a single IAS should follow a similar logistic curve. While the precise shape of the curve may depend on case-specific details (e.g., on the environmental properties or stage of invasion), the assumption of logistic IAS impacts has lacked large-scale empirical testing until recently (Ahmed et al 2021;Cuthbert et al 2022). Despite previous evidence for cost saturation, it is also possible that costs of an IAS may not plateau in the long term, with sustained cost increases potentially attributable to continual impacts on existing or new socioeconomic sectors coupled with ineffective long-term management.…”

“…This assumption is supported by empirical cost data for several taxa (Diagne et al 2020b), where reported costs at large timescales can be several orders of magnitude smaller than the reported maximum cost, indicating a trend towards null costs. As a result, cumulative management and damage costs saturate at their respective cost carrying capacities (see Ahmed et al 2021). Building upon this, we formulate a theoretical cost model for marginal, realized damage costs and for the total expenditure (inclusive of damage and management costs), whilst allowing for variable management delay times and time-dependent management efficiencies.…”

Surprisingly high economic costs of biological invasions in protected areas

“…This pattern may extend beyond PAs, as this type of reactive management has also been noted in non-PAs of Central and South America (Heringer et al 2021). Further, the dominance of post-invasion management expenditure points to the need for more preventative measures, such as biosecurity, to curtail the increased expenses associated with post-invasion management (Leung et al 2002;Ahmed et al 2021). Given that preserving biodiversity is one of the main goals of PAs (although in some cases goals are combined with others depending on the management category of the PA; see https:// www.…”

Economic costs of invasive bivalves in freshwater ecosystems

“…However, while categorizations for invader socio-economic impacts have been designed (Bacher et al, 2017), there remains a paucity of quantified socioeconomic costs for key taxonomic groups, hampering effective cost-benefit analysis and rationale for policymakers to invest the sparse available resources towards prevention and control (but see Cuthbert, Pattison, et al, 2021;Diagne et al, 2021, for analyses at the global scale across taxa). This constraint to invest still exists even though it has been shown that preventive measures are generally considered more cost-effective than long-term damages and control (Ahmed et al, 2021;Keller et al, 2008), with pre-invasion management remaining underfunded (Leung et al, 2002). Indeed, proactive preventative measures have the potential to yield trillion-dollar savings over just a few decades compared with delayed management actions (Cuthbert et al, 2022).…”