Prediction of viral spillover risk based on the mass action principle.

Infectious zoonotic disease emergence, through spillover events, is of global concern and has the potential to cause significant harm to society, as recently demonstrated by COVID-19. More than 70% of the 400 infectious diseases that emerged in the past five decades have a zoonotic origin, including all recent pandemics. There have been several approaches used to predict the risk of spillover through some of the known or suspected infectious disease emergence drivers, largely using correlative approaches. Here, we predict the spatial distribution of spillover risk by approximating general transmission through animal and human interactions. These mass action interactions are approximated through the multiplication of the spatial distribution of zoonotic virus diversity and human population density. Although our results indicate higher risk in regions along the equator and in Southeast Asia where both virus diversity and human population density are high, it should be noted that this is primarily a conceptual exercise. We compared our spillover risk map to key factors, including the model inputs of zoonotic virus diversity estimate map, human population density map, and the spatial distribution of species richness. Despite the limitations of this approach, this viral spillover map is a step towards developing a more comprehensive spillover risk prediction system to inform global monitoring.

Native turncoats and indirect facilitation of species invasions.

At local scales, native species can resist invasion by feeding on and competing with would-be invasive species. However, this relationship tends to break down or reverse at larger scales. Here, we consider the role of native species as indirect facilitators of invasion and their potential role in this diversity-driven 'invasion paradox'. We coin the term 'native turncoats' to describe native facilitators of non-native species and identify eight ways they may indirectly facilitate species invasion. Some are commonly documented, while others, such as indirect interactions within competitive communities, are largely undocumented in an invasion context. Therefore, we use models to evaluate the likelihood that these competitive interactions influence invasions. We find that native turncoat effects increase with the number of resources and native species. Furthermore, our findings suggest the existence, abundance and effectiveness of native turncoats in a community could greatly influence invasion success at large scales.

Global threat to agriculture from invasive species.

Invasive species present significant threats to global agriculture, although how the magnitude and distribution of the threats vary between countries and regions remains unclear. Here, we present an analysis of almost 1,300 known invasive insect pests and pathogens, calculating the total potential cost of these species invading each of 124 countries of the world, as well as determining which countries present the greatest threat to the rest of the world given their trading partners and incumbent pool of invasive species. We find that countries vary in terms of potential threat from invasive species and also their role as potential sources, with apparently similar countries sometimes varying markedly depending on specifics of agricultural commodities and trade patterns. Overall, the biggest agricultural producers (China and the United States) could experience the greatest absolute cost from further species invasions. However, developing countries, in particular, Sub-Saharan African countries, appear most vulnerable in relative terms. Furthermore, China and the United States represent the greatest potential sources of invasive species for the rest of the world. The analysis reveals considerable scope for ongoing redistribution of known invasive pests and highlights the need for international cooperation to slow their spread.

Birds of a feather: using species assemblages to assess vulnerability to extinction.

Estimating extinction vulnerability for a large number of species presents significant challenges for researchers, but is of high importance considering the large number of species that are currently unassessed. We present a method using a type of artificial neural network (self organizing map; SOM), which utilizes the co-occurrence patterns of species to estimate each species' vulnerability to extinction. We use this method on Australian bird assemblages and compare the SOM-generated rankings for vulnerability with assessments from the IUCN Red List for those species in which populations have actually been estimated. For species that have had their populations estimated, the SOM performed well in distinguishing those species ranked of least concern by IUCN from those species in one of the other IUCN categories. Further, 19 species that were identified as highly vulnerable by the SOM analysis have never had their populations estimated and have been ranked by the IUCN of least concern. We show how the SOM can identify spatial variation in vulnerability for a species, and identify those regions in Australia in which the resident species have the greatest levels of vulnerability (central Australia). We conclude that the SOM provides a useful tool for researchers and agencies dealing with conservation strategies focused on large numbers of species and we urge a more detailed assessment of the 19 bird species identified by this analysis as vulnerable to extinction.

Quantifying the Establishment Likelihood of Invasive Alien Species Introductions Through Ports with Application to Honeybees in Australia.

The cost of an uncontrolled incursion of invasive alien species (IAS) arising from undetected entry through ports can be substantial, and knowledge of port-specific risks is needed to help allocate limited surveillance resources. Quantifying the establishment likelihood of such an incursion requires quantifying the ability of a species to enter, establish, and spread. Estimation of the approach rate of IAS into ports provides a measure of likelihood of entry. Data on the approach rate of IAS are typically sparse, and the combinations of risk factors relating to country of origin and port of arrival diverse. This presents challenges to making formal statistical inference on establishment likelihood. Here we demonstrate how these challenges can be overcome with judicious use of mixed-effects models when estimating the incursion likelihood into Australia of the European (Apis mellifera) and Asian (A. cerana) honeybees, along with the invasive parasites of biosecurity concern they host (e.g., Varroa destructor). Our results demonstrate how skewed the establishment likelihood is, with one-tenth of the ports accounting for 80% or more of the likelihood for both species. These results have been utilized by biosecurity agencies in the allocation of resources to the surveillance of maritime ports.

Global establishment risk of economically important fruit fly species (Tephritidae).

The global invasion of Tephritidae (fruit flies) attracts a great deal of attention in the field of plant quarantine and invasion biology because of their economic importance. Predicting which one in hundreds of potential invasive fruit fly species is most likely to establish in a region presents a significant challenge, but can be facilitated using a self organising map (SOM), which is able to analyse species associations to rank large numbers of species simultaneously with an index of establishment. A global presence/absence dataset including 180 economically significant fruit fly species in 118 countries was analysed using a SOM. We compare and contrast ranked lists from six countries selected from each continent, and also show that those countries geographically close were clustered together by the SOM analysis because they have similar fruit fly assemblages. These closely clustered countries therefore represent greater threats to each other as sources of invasive fruit fly species. Finally, we indicate how this SOM method could be utilized as an initial screen to support prioritizing fruit fly species for further research into their potential to invade a region.

Can global weed assemblages be used to predict future weeds?

Predicting which plant taxa are more likely to become weeds in a region presents significant challenges to both researchers and government agencies. Often it is done in a qualitative or semi-quantitative way. In this study, we explored the potential of using the quantitative self-organising map (SOM) approach to analyse global weed assemblages and estimate likelihoods of plant taxa becoming weeds before and after they have been moved to a new region. The SOM approach examines plant taxa associations by analysing where a taxon is recorded as a weed and what other taxa are recorded as weeds in those regions. The dataset analysed was extracted from a pre-existing, extensive worldwide database of plant taxa recorded as weeds or other related status and, following reformatting, included 187 regions and 6690 plant taxa. To assess the value of the SOM approach we selected Australia as a case study. We found that the key and most important limitation in using such analytical approach lies with the dataset used. The classification of a taxon as a weed in the literature is not often based on actual data that document the economic, environmental and/or social impact of the taxon, but mostly based on human perceptions that the taxon is troublesome or simply not wanted in a particular situation. The adoption of consistent and objective criteria that incorporate a standardized approach for impact assessment of plant taxa will be necessary to develop a new global database suitable to make predictions regarding weediness using methods like SOM. It may however, be more realistic to opt for a classification system that focuses on the invasive characteristics of plant taxa without any inference to impacts, which to be defined would require some level of research to avoid bias from human perceptions and value systems.

Modelling the arrival of invasive organisms via the international marine shipping network: a Khapra beetle study.

Species can sometimes spread significant distances beyond their natural dispersal ability by anthropogenic means. International shipping routes and the transport of shipping containers, in particular are a commonly recognised pathway for the introduction of invasive species. Species can gain access to a shipping container and remain inside, hidden and undetected for long periods. Currently, government biosecurity agencies charged with intercepting and removing these invasive species when they arrive to a county's border only assess the most immediate point of loading in evaluating a shipping container's risk profile. However, an invasive species could have infested a container previous to this point and travelled undetected before arriving at the border. To assess arrival risk for an invasive species requires analysing the international shipping network in order to identify the most likely source countries and the domestic ports of entry where the species is likely to arrive. We analysed an international shipping network and generated pathway simulations using a first-order Markov chain model to identify possible source ports and countries for the arrival of Khapra beetle (Trogoderma granarium) to Australia. We found Kaohsiung (Taiwan) and Busan (Republic of Korea) to be the most likely sources for Khapra beetle arrival, while the port of Melbourne was the most likely point of entry to Australia. Sensitivity analysis revealed significant stability in the rankings of foreign and Australian ports. This methodology provides a reliable modelling tool to identify and rank possible sources for an invasive species that could arrive at some time in the future. Such model outputs can be used by biosecurity agencies concerned with inspecting incoming shipping containers and wishing to optimise their inspection protocols.

Biosecurity and yield improvement technologies are strategic complements in the fight against food insecurity.

The delivery of food security via continued crop yield improvement alone is not an effective food security strategy, and must be supported by pre- and post-border biosecurity policies to guard against perverse outcomes. In the wake of the green revolution, yield gains have been in steady decline, while post-harvest crop losses have increased as a result of insufficiently resourced and uncoordinated efforts to control spoilage throughout global transport and storage networks. This paper focuses on the role that biosecurity is set to play in future food security by preventing both pre- and post-harvest losses, thereby protecting crop yield. We model biosecurity as a food security technology that may complement conventional yield improvement policies if the gains in global farm profits are sufficient to offset the costs of implementation and maintenance. Using phytosanitary measures that slow global spread of the Ug99 strain of wheat stem rust as an example of pre-border biosecurity risk mitigation and combining it with post-border surveillance and invasive alien species control efforts, we estimate global farm profitability may be improved by over US$4.5 billion per annum.

Predicting invasive fungal pathogens using invasive pest assemblages: testing model predictions in a virtual world.

Predicting future species invasions presents significant challenges to researchers and government agencies. Simply considering the vast number of potential species that could invade an area can be insurmountable. One method, recently suggested, which can analyse large datasets of invasive species simultaneously is that of a self organising map (SOM), a form of artificial neural network which can rank species by establishment likelihood. We used this method to analyse the worldwide distribution of 486 fungal pathogens and then validated the method by creating a virtual world of invasive species in which to test the SOM. This novel validation method allowed us to test SOM's ability to rank those species that can establish above those that can't. Overall, we found the SOM highly effective, having on average, a 96-98% success rate (depending on the virtual world parameters). We also found that regions with fewer species present (i.e. 1-10 species) were more difficult for the SOM to generate an accurately ranked list, with success rates varying from 100% correct down to 0% correct. However, we were able to combine the numbers of species present in a region with clustering patterns in the SOM, to further refine confidence in lists generated from these sparsely populated regions. We then used the results from the virtual world to determine confidences for lists generated from the fungal pathogen dataset. Specifically, for lists generated for Australia and its states and territories, the reliability scores were between 84-98%. We conclude that a SOM analysis is a reliable method for analysing a large dataset of potential invasive species and could be used by biosecurity agencies around the world resulting in a better overall assessment of invasion risk.

Threat of invasive pests from within national borders.

Predicting and ranking potential invasive species present significant challenges to researchers and biosecurity agencies. Here we analyse a worldwide database of pest species assemblages to generate lists of the top 100 insect pests most likely to establish in the United States and each of its 48 contiguous states. For the United States as a whole, all of the top 100 pest species have already established. Individual states however tend to have many more 'gaps' with most states having at least 20 species absent from their top 100 list. For all but one state, every exotic pest species currently absent from a state's top 100 can be found elsewhere in the contiguous United States. We conclude that the immediate threat from known invasive insect pests is greater from within the United States than without. Our findings have potentially significant implications for biosecurity policy, emphasizing the need to consider biosecurity measures beyond established national border interventions.

Dispersal, patch leaving, and distribution of Homalodisca vitripennis (Hemiptera: Cicadellidae).

Homalodisca vitripennis (Germar) and related species have caused millions of dollars in damage to southern California vineyards in recent years through the vectoring of Pierce's disease. However, the effects of surrounding vegetation on the dispersal and distribution of H. vitripennis are poorly understood. Therefore, the relationship between dispersal rates and patch quality was tested, as well as the basic predictions of the marginal value theorem. Additional experiments were conducted to compare the H. vitripennis distribution in an isolated crape myrtle (Lagerstroemia indica) patch and a L. indica patch bordering two alternative host patches. In mark-release-recapture tests, H. vitripennis dispersed farther from the release point in a patch of low-quality host plants (Prunus persica) than in patches of high-quality host plants (L. indica). In addition, H. vitripennis remained in L. indica patches longer than in P. persica patches and adjusted patch residence times in P. persica in correlation with known changes in plant physiology. These data suggest that H. vitripennis follows the basic predictions of marginal value theorem. In distribution tests, H. vitripennis were more abundant in the patch center than patch edges in the isolated L. indica patch, but in a patch bordering cottonwood (Populus sp.) and peach (P. persica), H. vitripennis numbers were generally higher along the edges of the patch. These data suggest that alternate hosts bordering cropping systems may be important to the spatial dynamics of H. vitripennis. Implications of these spatial observations on the biology of H. vitripennis and potential control methods are discussed.

Competitive exclusion of a worldwide invasive pest by a native. Quantifying competition between two phytophagous insects on two host plant species.

1. High competitive ability is believed to be an important characteristic of invasive species. Many animal studies have compared the competitive ability of invasive species with a native species that is being displaced, but few have looked at systems where an invasive species has failed to establish itself. These types of studies are important to determine if competition is relevant not only to invading species but also to the biotic resistance of a community. 2. The thrips species F. occidentalis is a highly invasive pest that has spread from its original range (the western states of the USA) to a worldwide distribution. Despite this, F. occidentalis is largely absent or occurs in low numbers in the eastern states of the USA, where the native F. tritici dominates. It is possible that F. tritici is competitively excluding F. occidentalis from this region. 3. Larval competition between these two thrips species was tested on two known plant hosts, Capsicum annuum (a crop plant), and Raphanus raphanistrum (an invasive weed), using a response surface design with number of larvae surviving as the response variable. The response surface design allowed competition models to be fit to data using maximum likelihood estimation, thus generating quantitative values for interspecific competition. 4. On both plant hosts, the native F. tritici did not experience significant interspecific competition from the invasive F. occidentalis. In contrast, F. occidentalis did experience significant interspecific competition from F. tritici. Competition from F. tritici larvae on F. occidentalis larvae was estimated to be 1.72 times (on C. annuum) and 1.76 times (on R. raphanistrum) the effect of intraspecific competition. The invasive F. occidentalis appears to be competitively excluded by the native F. tritici. 5. This study confirms the importance of competition in the biotic resistance of a community and is one of the few animal studies to not only test for competition in an apparently resistant ecosystem but also to quantify the level of interspecific competition between two animal species.