Abstract
Invasive rodent populations pose a threat to biodiversity across the globe. When confronted with these invaders, native species that evolved independently are often defenseless. CRISPR gene drive systems could provide a solution to this problem by spreading transgenes among invaders that induce population collapse, and could be deployed even where traditional control methods are impractical or prohibitively expensive. Here, we develop a high-fidelity model of an island population of invasive rodents that includes three types of suppression gene drive systems. The individual-based model is spatially explicit, allows for overlapping generations and a fluctuating population size, and includes variables for drive fitness, efficiency, resistance allele formation rate, as well as a variety of ecological parameters. The computational burden of evaluating a model with such a high number of parameters presents a substantial barrier to a comprehensive understanding of its outcome space. We therefore accompany our population model with a meta-model that utilizes supervised machine learning to approximate the outcome space of the underlying model with a high degree of accuracy. This enables us to conduct an exhaustive inquiry of the population model, including variance-based sensitivity analyses using tens of millions of evaluations. Our results suggest that sufficiently capable gene drive systems have the potential to eliminate island populations of rodents under a wide range of demographic assumptions, though only if resistance can be kept to a minimal level. This study highlights the power of supervised machine learning to identify the key parameters and processes that determine the population dynamics of a complex evolutionary system.
Highlights
Global commerce webs and rapid human migration patterns that have arisen over the last several hundred years have resulted in the spread of various invasive species across the globe [1]
We evaluated the accuracy of our Gaussian process (GP) models by assessing root-meansquare error (RMSE) between actual output generated by the population model and the output predicted by the GP models, as well as by measuring precision and recall
We first examined the population model in the absence of any gene drive release in order to verify that the model dynamics are reasonable and generally match our expectations of rat population dynamics
Summary
Global commerce webs and rapid human migration patterns that have arisen over the last several hundred years have resulted in the spread of various invasive species across the globe [1]. Some ecosystems are highly vulnerable to disruption by these invaders, resulting in severe ecological consequences to endemic species. Rodents such as rats can be damaging when introduced to remote islands, where they may find themselves completely without predators. Local eradication of invasive rat species is a critical conservation strategy on islands where the invaders threaten endemic species. Eradication efforts on small and medium-sized islands have successfully protected endangered species from extinction [3]. If even a small remnant of invaders survives, the population can rapidly bounce back after control efforts cease This means that impactful results cannot be achieved unless these strategies are applied continuously [4]. There is a clear and urgent need for new approaches to combat invasive rodent species in order to preserve native biological diversity
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