The United States has thousands of invasive species, representing a sizable, but unknown burden to the national economy. Given the potential economic repercussions of invasive species, quantifying these costs is of paramount importance both for national economies and invasion management. Here, we used a novel global database of invasion costs (InvaCost) to quantify the overall costs of invasive species in the United States across spatiotemporal, taxonomic, and socioeconomic scales. From 1960 to 2020, reported invasion costs totaled $4.52 trillion (USD 2017). Considering only observed, highly reliable costs, this total cost reached $1.22 trillion with an average annual cost of $19.94 billion/year. These costs increased from $2.00 billion annually between 1960 and 1969 to $21.08 billion annually between 2010 and 2020. Most costs (73%) were related to resource damages and losses ($896.22 billion), as opposed to management expenditures ($46.54 billion). Moreover, the majority of costs were reported from invaders from terrestrial habitats ($643.51 billion, 53%) and agriculture was the most impacted sector ($509.55 billion). From a taxonomic perspective, mammals ($234.71 billion) and insects ($126.42 billion) were the taxonomic groups responsible for the greatest costs. Considering the apparent rising costs of invasions, coupled with increasing numbers of invasive species and the current lack of cost information for most known invaders, our findings provide critical information for policymakers and managers.

Controlling Ebola outbreaks and planning an effective response to future emerging diseases are enhanced by understanding the role of geography in transmission. Here we show how epidemic expansion may be predicted by evaluating the relative probability of alternative epidemic paths. We compared multiple candidate models to characterize the spatial network over which the 2013–2015 West Africa epidemic of Ebola virus spread and estimate the effects of geographical covariates on transmission during peak spread. The best model was a generalized gravity model where the probability of transmission between locations depended on distance, population density and international border closures between Guinea, Liberia and Sierra Leone and neighbouring countries. This model out-performed alternative models based on diffusive spread, the force of infection, mobility estimated from cell phone records and other hypothesized patterns of spread. These findings highlight the importance of integrated geography to epidemic expansion and may contribute to identifying both the most vulnerable unaffected areas and locations of maximum intervention value.

Wildlife and plant diseases can reduce biodiversity, disrupt ecosystem services and threaten human health. Emerging pathogens have displayed a variety of spatial spread patterns due to differences in host ecology, including diffusive spread from an epicentre (West Nile virus), jump dispersal on a network (foot-and-mouth disease), or a combination of these (Sudden oak death). White-nose syndrome is a highly pathogenic infectious disease of bats currently spreading across North America. Understanding how bat ecology influences this spread is crucial to management of infected and vulnerable populations. Here we show that white-nose syndrome spread is not diffusive but rather mediated by patchily distributed habitat and large-scale gradients in winter climate. Simulations predict rapid expansion and infection of most counties with caves in the contiguous United States by winter 2105–2106. Our findings show the unique pattern of white-nose syndrome spread corresponds to ecological traits of the host and suggest hypotheses for transmission mechanisms acting at the local scale.

Summary: 1.Allee effects may result in negative growth rates at low population density, with important implications for conservation and management of exploited populations. Theory predicts prey populations will exhibit Allee effects when their predator exhibits a Type II functional response, but empirical evidence linking this positively density‐dependent variation in predator‐induced individual mortality to population growth rate and probability of extinction is lacking.2.Here, we report a demonstration of extinction due to predator‐driven Allee effects in an experimentalDaphnia‐Chaoborussystem. A component Allee effect caused by higher predation rates at lowDaphniadensity led to positive density dependence in per capita growth rate and accelerated extinction rate at low density.3.A stochastic model of the process revealed how the critical density below which population growth is negative depends on the mechanistic details of the predator–prey interaction.4.The ubiquity of predator–prey interactions and saturating functional responses suggests predator‐driven Allee effects are potentially important in determining extinction risk of a large number of species.