Predicting the spread of all invasive forest pests in the United States

Future Climate Change and Anthropogenic Disturbance Promote the Invasions of the World's Worst Invasive Insect Pests

Invasive insect pests adversely impact human welfare and global ecosystems. However, no studies have used a unified scheme to compare the range dynamics of the world's worst invasive insect pests. We investigated the future range shifts of 15 of the world's worst invasive insect pests. Although future range dynamics varied substantially among the 15 worst invasive insect pests, most exhibited large range expansions. Increases in the total habitat suitability occurred in more than ca. 85% of global terrestrial regions. The relative impacts of anthropogenic disturbance and climate variables on the range dynamics depended on the species and spatial scale. Aedes albopictus, Cinara cupressi, and Trogoderma granarium occurred four times in the top five largest potential ranges under four future climate scenarios. Anoplophora glabripennis, Aedes albopictus, and Co. formosanus were predicted to have the largest range expansions. An. glabripennis, Pl. manokwari, Co. formosanus, and So. invicta showed the largest range centroid shifts. More effective strategies will be required to prevent their range expansions. Although the strategies should be species-specific, mitigating anthropogenic disturbances and climate change will be essential to preventing future invasions. This study provides critical and novel insights for developing global strategies to combat the invasions of invasive insect pests in the future.

Hosts and impacts of elongate hemlock scale (Hemiptera: Diaspididae): A critical review

Fiorinia externa Ferris, elongate hemlock scale, was inadvertently introduced to North America from Japan. This insect is particularly problematic on hemlock, Tsuga spp., though it has been reported in association with several other conifers. The evidence that other conifers might be hosts, capable of supporting growing populations of the insect, has not been previously reviewed. Our review confirms that F. externa is an oligophagous pest of members of Pinaceae. Although species of Cupressaceae and Taxaceae have been reported as hosts of F. externa, they seem unable to support population growth of this pest. Evidence of the tree-killing potential of the insect, even on suitable hosts, is remarkably scant. The degree of pest risk posed by F. externa with respect to tree mortality in areas beyond the geographic range of hemlock seems modest, but uncertain.

Climate match is key to predict range expansion of the world's worst invasive terrestrial vertebrates

Understanding the determinants of the range expansion of invasive alien species is crucial for developing effective prevention and control strategies. Nevertheless, we still lack a global picture of the potential factors influencing the invaded range expansion across taxonomic groups, especially for the world's worst invaders with high ecological and economic impacts. Here, by extensively collecting data on 363 distributional ranges of 19 of world's worst invasive terrestrial vertebrates across 135 invaded administrative jurisdictions, we observed remarkable variations in the range expansion across species and taxonomic groups. After controlling for taxonomic and geographic pseudoreplicates, model averaging analyses based on generalized additive mixed-effect models showed that species in invaded regions having climates more similar to those of their native ranges tended to undergo a larger range expansion. In addition, as proxies of propagule pressure and human-assisted transportation, the number of introduction events and the road network density were also important predictors facilitating the range expansion. Further variance partitioning analyses validated the predominant role of climate match in explaining the range expansion. Our study demonstrated that regions with similar climates to their native ranges could still be prioritized to prevent the spread of invasive species under the sustained global change.

Popillia japonica - Italian outbreak management

Popillia japonica, a priority pest for the EU, was first detected in Northern Italy in 2014. Since its discovery, the outbreak extended over an area of more than 16,000 square kilometers in Northern Italy and Southern Switzerland. In this review, we summarize the state-of-the-art of research conducted in Italy on both the spreading capacity and control measures of P. japonica. Chemical, physical, and biological control measures deployed since its detection are presented, by highlighting their strengths and weaknesses. An in-depth study of the ecosystems invaded by P. japonica disclosed the presence and pathogenicity of natural strains of entomopathogenic fungi and nematodes, some of which have shown to be particularly aggressive towards the larvae of this pest under laboratory conditions. The Plant Health authorities of the Lombardy and Piedmont regions, with the support of several research institutions, played a crucial role in the initial eradication attempt and subsequently in containing the spread of P. japonica. Control measures were performed in the infested area to suppress adult populations of P. japonica by installing several traps (e.g., for mass trapping, for auto-dissemination of the fungus Metarhizium anisopliae, and "attract & kill"). For larval control, the infested fields were treated with commercial strains of the entomopathogenic fungus M. anisopliae and nematode Heterorhabditis bacteriophora. Future studies will aim at integrating phenological and spread models developed with the most effective control measures, within an ecologically sustainable approach.

Warm temperatures and host tree abundance explain variation in directional spread by laurel wilt

The rate at which invading organisms disperse into novel habitats is fundamental to their distribution and abundance. Forecasts of spread often assume that invasion speed is constant through time and among directions but, depending on the extent to which this assumption is violated, the efficacy of delimitation surveys and eradication programs could suffer. Knowledge of the mechanisms underlying spatiotemporal variation in spread could help refine forecasts and guide management, particularly in the early stages of invasions. We investigated rates of spread by laurel wilt, one of the most damaging non-native forest pests in North America, using three standard approaches (effective range radius, distance regression, and boundary displacement) and evaluated the strength and drivers of variation in directional spread (i.e., anisotropy). Estimates of mean annual spread varied from 24 to 40 km/yr, but spread was highly anisotropic with invasion speeds reaching approximately 100 km/yr south, 80 km/yr west, and 50 km/yr north, a pattern that we attribute to the abundance of host redbay trees and warmer temperatures fostering rapid southern and western spread. This pattern-quicker spread of laurel wilt from the point of introduction into areas forecasted as highly suitable for its persistence-suggests that establishment location might have a major influence on rates of anisotropy. Our findings underscore the utility of habitat suitability modeling-in which host availability and suitable climate are widely used to forecast establishment risk-for identifying areas into which spread will proceed most rapidly following establishment of a new invader and/or a satellite population via a long-distance dispersal event.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10530-023-03069-5.

Phylogenetic risk assessment is robust for forecasting the impact of European insects on North American conifers

Some introduced species cause severe damage, although the majority have little impact. Robust predictions of which species are most likely to cause substantial impacts could focus efforts to mitigate those impacts or prevent certain invasions entirely. Introduced herbivorous insects can reduce crop yield, fundamentally alter natural and managed forest ecosystems, and are unique among invasive species in that they require certain host plants to succeed. Recent studies have demonstrated that understanding the evolutionary history of introduced herbivores and their host plants can provide robust predictions of impact. Specifically, divergence times between hosts in the native and introduced ranges of a nonnative insect can be used to predict the potential impact of the insect should it establish in a novel ecosystem. However, divergence time estimates vary among published phylogenetic datasets, making it crucial to understand if and how the choice of phylogeny affects prediction of impact. Here, we tested the robustness of impact prediction to variation in host phylogeny by using insects that feed on conifers and predicting the likelihood of high impact using four different published phylogenies. Our analyses ranked 62 insects that are not established in North America and 47 North American conifer species according to overall risk and vulnerability, respectively. We found that results were robust to the choice of phylogeny. Although published vascular plant phylogenies continue to be refined, our analysis indicates that those differences are not substantial enough to alter the predictions of invader impact. Our results can assist in focusing biosecurity programs for conifer pests and can be more generally applied to nonnative insects and their potential hosts by prioritizing surveillance for those insects most likely to be damaging invaders.

Where to search: the use of opportunistic data for the detection of an invasive forest pest

Early detection is important for the management of invasive alien species. In the last decade citizen science has become an important source of such data. Here, we used opportunistic records from the “LIFE ARTEMIS” citizen science project, in which people submitted records from places where they observed tree pests, to understand the distribution of a rapidly-spreading forest pest: the oak lace bug (Corythucha arcuata) in Slovenia. These citizen science records were not distributed randomly. We constructed a species distribution model for C. arcuata that accounted for the biased distribution of citizen science by using the records of other tree pests and diseases from the same project as pseudo-absences (so-called constrained pseudo-absences), and compared this to a model with pseudo-absences selected randomly from across Slovenia. We found that the constrained pseudo-absence model showed that C. arcuata was more likely to be found in east, in places with more oak trees and at lower elevations, and also closer to highways and railways, indicating introduction and dispersal by accidental human transport. The outputs from the model with random pseudo-absences were broadly similar, although estimates from this model tended to be higher and less precise, and some factors that were significant (proximity to minor roads and human settlements) were artefacts of recorder bias, showing the importance of taking the distribution of recording into account wherever possible. The finding that C. arcuata is more likely to be found near highways allows us to design advice for where future citizen science should be directed for efficient early detection.

Flight Mill Experiments and Computer Simulations Indicate Islands Recruit More Capable Flyers of Moths

Understanding the traits related to species colonization and invasion, is a key question for both pest management and evolution. One of the key components is flight, which has been measured for a number of insect species through radar and tethered flight mill systems, but a general understanding of insect flight at a community level is lacking. In this study, we used flight mill experiments to quantify flight abilities of moth species, and simulation experiments to study which moths in mainland China have the potential for cross-island dispersal. We found that moths from superfamily Geometroidea (family Geometridae) have the weakest flight ability among the seven Lepidoptera superfamilies, which is characterized by the shortest longest single flight (LSF), the shortest time corresponding to the longest single flight (TLSF) (timecorrespondingtothelongestsingleflight), the lowest total distance flown (TDF), and the lowest average speed during the flight (VTDF). Surprisingly, the family Pyralidae (superfamily Pyraloidea) has the highest flight endurance of all 186 species of 12 families in this study, which is unexpected, given its small size and morphological traits yet it shows the longest LSF and TLSF. The comparison between species common to mainland and islands shows that flight distance (LSF) may be more important for species spread than flight speed. The results of mainland-island simulations show that when P(LSF>CD) (the proportion of individuals whose LSF is greater than the closest distance (CD) between mainland and island to the total number of individuals in the population) is less than 0.004, it is difficult for moth species to disperse to across islands without relying on external factors such as airflow. Over extended periods, with the immigration of species with strong flight abilities, islands are more likely to recruit species with stronger flight abilities.

Non-native plant drives the spatial dynamics of its herbivores: the case of black locust (Robinia pseudoacacia) in Europe

Non-native plants typically benefit from enemy release following their naturalization in non-native habitats. However, over time, herbivorous insects specializing on such plants may invade from the native range and thereby diminish the benefits of enemy release that these plants may experience. In this study, we compare rates of invasion spread across Europe of three North American insect folivores: the Lepidoptera leaf miners Macrosaccus robiniella and Parectopa robiniella, and the gall midge Obolodiplosis robiniae, that specialize on Robinia pseudoacacia. This tree species is one of the most widespread non-native trees in Europe. We find that spread rates vary among the three species and that some of this variation can be explained by differences in their life history traits. We also report that geographical variation in spread rates are influenced by distribution of Robinia pseudoacacia, human population and temperature, though Robinia pseudoacacia occurrence had the greatest influence. The importance of host tree occurrence on invasion speed can be explained by the general importance of hosts on the population growth and spread of invading species.

Long-Term Projections of the Natural Expansion of the Pine Wood Nematode in the Iberian Peninsula

The invasive pine wood nematode (PWN), Bursaphelenchus xylophilus, causal agent of pine wilt disease, was first reported in Europe, near Lisbon, in 1999, and has since then spread to most of Portugal. We here modelled the spatiotemporal patterns of future PNW natural spread in the Iberian Peninsula, as dispersed by the vector beetle Monochamus galloprovincialis, using a process-based and previously validated network model. We improved the accuracy, informative content, forecasted period and spatial drivers considered in previous modelling efforts for the PWN in Southern Europe. We considered the distribution and different susceptibility to the PWN of individual pine tree species and the effect of climate change projections on environmental suitability for PWN spread, as we modelled the PWN expansion dynamics over the long term (>100 years). We found that, in the absence of effective containment measures, the PWN will spread naturally to the entire Iberian Peninsula, including the Pyrenees, where it would find a gateway for spread into France. The PWN spread will be relatively gradual, with an average rate of 0.83% of the total current Iberian pine forest area infected yearly. Climate was not found to be an important limiting factor for long-term PWN spread, because (i) there is ample availability of alternative pathways for PWN dispersal through areas that are already suitable for the PWN in the current climatic conditions; and (ii) future temperatures will make most of the Iberian Peninsula suitable for the PWN before the end of this century. Unlike climate, the susceptibility of different pine tree species to the PWN was a strong determinant of PWN expansion through Spain. This finding highlights the importance of accounting for individual tree species data and of additional research on species-specific susceptibility for more accurate modelling of PWN spread and guidance of related containment efforts.

Effects of Starvation, Age, and Mating Status on Flight Capacity of Laboratory-Reared Brown Marmorated Stink Bug (Hemiptera: Pentatomidae)

The brown marmorated stink bug, Halyomorpha halys (Stål) (Hemiptera: Pentatomidae), is an invasive species to North America and has spread throughout most of the territory. Understanding flight in H. halys is crucial to understanding the dispersal capacity and developing forecasting models for this pest. The purpose of this research was to assess the effects of starvation, age, mating status, sex, and preflight weight on flight parameters of laboratory-reared H. halys using computer-monitored flight mills. The mean flight distance observed over a 24-h period was 266 m and the maximum distance was 7.3 km. Overall, the flight capacity of males and females was similar, even though females weighed more than males. The proportion of H. halys that initiated flight was not affected by starvation, age, or mating status. The number of bouts of individual flights and velocity significantly increased with longer durations of starvation. The number of bouts significantly decreased with increasing age. The total distance flew and total flight time was not affected by starvation, age, or mating status. Although some statistical differences were seen across the experiments, these differences likely represent minimal ecological significance. Therefore, these results suggest that H. halys are remarkably resilient, which may contribute to their success as an invasive species. The findings of this study could help better predict the dispersal potential of H. halys in Minnesota.

Modelling for risk and biosecurity related to forest health

Modelling the invasion and emergence of forest pests and pathogens (PnPs) is necessary to quantify the risk levels for forest health and provide key information for policy makers. Here, we make a short review of the models used to quantify the invasion risk of exotic species and the emergence risk of native species. Regarding the invasion process, models tackle each invasion phase, e.g. pathway models to describe the risk of entry, species distribution models to describe potential establishment, and dispersal models to describe (human-assisted) spread. Concerning the emergence process, models tackle each process: spread or outbreak. Only a few spread models describe jointly dispersal, growth, and establishment capabilities of native species while some mechanistic models describe the population temporal dynamics and inference models describe the probability of outbreak. We also discuss the ways to quantify uncertainty and the role of machine learning. Overall, promising directions are to increase the models’ genericity by parameterization based on meta-analysis techniques to combine the effect of species traits and various environmental drivers. Further perspectives consist in considering the models’ interconnection, including the assessment of the economic impact and risk mitigation options, as well as the possibility of having multi-risks and the reduction in uncertainty by collecting larger fit-for-purpose datasets.

Pathologists and entomologists must join forces against forest pest and pathogen invasions

The world’s forests have never been more threatened by invasions of exotic pests and pathogens, whose causes and impacts are reinforced by global change. However, forest entomologists and pathologists have, for too long, worked independently, used different concepts and proposed specific management methods without recognising parallels and synergies between their respective fields. Instead, we advocate increased collaboration between these two scientific communities to improve the long-term health of forests.

Our arguments are that the pathways of entry of exotic pests and pathogens are often the same and that insects and fungi often coexist in the same affected trees. Innovative methods for preventing invasions, early detection and identification of non-native species, modelling of their impact and spread and prevention of damage by increasing the resistance of ecosystems can be shared for the management of both pests and diseases.

We, therefore, make recommendations to foster this convergence, proposing in particular the development of interdisciplinary research programmes, the development of generic tools or methods for pest and pathogen management and capacity building for the education and training of students, managers, decision-makers and citizens concerned with forest health.

Impact of Xylella fastidiosa subspecies pauca in European olives

Xylella fastidiosa is the causal agent of plant diseases that cause massive economic damage. In 2013, a strain of the bacterium was, for the first time, detected in the European territory (Italy), causing the Olive Quick Decline Syndrome. We simulate future spread of the disease based on climatic-suitability modeling and radial expansion of the invaded territory. An economic model is developed to compute impact based on discounted foregone profits and losses in investment. The model projects impact for Italy, Greece, and Spain, as these countries account for around 95% of the European olive oil production. Climatic suitability modeling indicates that, depending on the suitability threshold, 95.5 to 98.9%, 99.2 to 99.8%, and 84.6 to 99.1% of the national areas of production fall into suitable territory in Italy, Greece, and Spain, respectively. For Italy, across the considered rates of radial range expansion the potential economic impact over 50 y ranges from 1.9 billion to 5.2 billion Euros for the economic worst-case scenario, in which production ceases after orchards die off. If replanting with resistant varieties is feasible, the impact ranges from 0.6 billion to 1.6 billion Euros. Depending on whether replanting is feasible, between 0.5 billion and 1.3 billion Euros can be saved over the course of 50 y if disease spread is reduced from 5.18 to 1.1 km per year. The analysis stresses the necessity to strengthen the ongoing research on cultivar resistance traits and application of phytosanitary measures, including vector control and inoculum suppression, by removing host plants.

Comparing generalized and customized spread models for nonnative forest pests

While generality is often desirable in ecology, customized models for individual species are thought to be more predictive by accounting for context specificity. However, fully customized models require more information for focal species. We focus on pest spread and ask: How much does predictive power differ between generalized and customized models? Further, we examine whether an intermediate "semi-generalized" model, combining elements of a general model with species-specific modifications, could yield predictive advantages. We compared predictive power of a generalized model applied to all forest pest species (the generalized dispersal kernel or GDK) to customized spread models for three invasive forest pests (beech bark disease [Cryptococcus fagisuga], gypsy moth [Lymantria dispar], and hemlock woolly adelgid [Adelges tsugae]), for which time-series data exist. We generated semi-generalized dispersal kernel models (SDK) through GDK correction factors based on additional species-specific information. We found that customized models were more predictive than the GDK by an average of 17% for the three species examined, although the GDK still had strong predictive ability (57% spatial variation explained). However, by combining the GDK with simple corrections into the SDK model, we attained a mean of 91% of the spatial variation explained, compared to 74% for the customized models. This is, to our knowledge, the first comparison of general and species-specific ecological spread models' predictive abilities. Our strong predictive results suggest that general models can be effectively synthesized with context-specific information for single species to respond quickly to invasions. We provided SDK forecasts to 2030 for all 63 United States pests in our data set.

Will growing invasive arthropod biodiversity outpace our ability for eradication?

The Global Eradication Database documents 811 eradication attempts against invasive arthropods since 1890, in 104 countries. Eradication programs show a greater than exponential increase in the number of programs started in recent decades. In addition, there is a trend of a rapidly diversifying burden of the most severe threats. The species richness showed a three-fold increase in number of species under eradication in the last 50 yr, and all taxonomic levels rose dramatically. The increase in number of eradication programs shows that current management measures for constraining the spread of invasive species are inadequate. A similar surge in the number of governments trying to prevent the establishment of new pests has occurred. Increased biodiversity of arthropod eradication targets includes new pest groups with fewer tools developed for management. We argue that a rapid increase in biodiversity of invasive and economically or environmentally damaging organisms represents a substantial and underestimated challenge for managers wanting to prevent their establishment, requiring a shift in research focus to accelerate delimitation and suppression options with less reliance on insecticides.

Towards a unified framework for connectivity that disentangles movement and mortality in space and time

Predicting connectivity, or how landscapes alter movement, is essential for understanding the scope for species persistence with environmental change. Although it is well known that movement is risky, connectivity modelling often conflates behavioural responses to the matrix through which animals disperse with mortality risk. We derive new connectivity models using random walk theory, based on the concept of spatial absorbing Markov chains. These models decompose the role of matrix on movement behaviour and mortality risk, can incorporate species distribution to predict the amount of flow, and provide both short- and long-term analytical solutions for multiple connectivity metrics. We validate the framework using data on movement of an insect herbivore in 15 experimental landscapes. Our results demonstrate that disentangling the roles of movement behaviour and mortality risk is fundamental to accurately interpreting landscape connectivity, and that spatial absorbing Markov chains provide a generalisable and powerful framework with which to do so.

Estimation of metapopulation colonization rates from disturbance history and occurrence-pattern data

Occurrence patterns of many sessile species in dynamic landscapes are not in equilibrium due to their slow rates of metapopulation colonization and extinction. Colonization-extinction data enable the estimation of colonization rates for such species, but collecting the necessary data may require long waiting times between sampling years. Methods for estimating colonization rates of nonequilibrium metapopulations from single occurrence-pattern data have so far relied on additional data on patch ages and on past patch connectivities. We present an approach where metapopulation colonization rates are estimated from occurrence-pattern data and from disturbance history data that inform of past patch dynamics and that can be collected together with occurrence-pattern data. We estimated parameter values regulating patch and metapopulation dynamics by simulating patch network and metapopulation histories that result in present-like patch network configurations and metapopulation occurrence patterns. We tested our approach using occurrence-pattern data of the epiphytic lichen Lobaria pulmonaria in Fennoscandian forests, and fire-scar data that inform of the 400-yr history of fires and host tree dynamics in the same landscapes. The estimated model parameters were similar to estimates obtained using colonization-extinction data. The projected L. pulmonaria occupancy into the future also agreed with the respective projections that were made using the model estimated from colonization-extinction data. Our approach accelerates the estimation of metapopulation colonization rates for sessile species that are not in metapopulation equilibrium with the current landscape structure.

Determining Spread Rate of Kudzu Bug (Hemiptera: Plataspidae) and Its Associations With Environmental Factors in a Heterogeneous Landscape

By the end of 2017, kudzu bug was reported in 652 counties in the United States since it was first observed in Georgia in 2009. Modeling its invasion dynamics is valuable to guide management through early detection and prevention of further invasion. Herein, we initially estimated the spread rate of kudzu bug with county-level invasion records and then determined important spatial factors affecting its spread during years 2010-2016. As kudzu bug infests a large heterogeneous area and shows asymmetric spread, we first utilized spatially constrained clustering (SCC), an unsupervised machine learning method, to divide the infested area into eight spatially contiguous and environmentally homogenous neighborhoods. We then used distance regression and boundary displacement methods to estimate the spread rates in all neighborhoods. Finally, we applied multiple regression to determine spatial factors influencing the spread of kudzu bug. The average spread rate reached 76 km/yr by boundary displacement method; however, the rate varied largely among eight neighborhoods (45-144 km/yr). In the southern region of the infested area, host plant density and wind speed were positively associated with the spread rate, whereas mean annual temperature, precipitation in the fall, and elevation had inverse relationships. In the northern region, January minimum temperature, wind speed, and human population density showed positive relationships. This study increases the knowledge on the spread dynamics of kudzu bug. Our research highlights the utility of SCC to determine natural clustering in a large heterogeneous region for better modeling of local spread patterns and determining important factors affecting the invasions.

Important Insect and Disease Threats to United States Tree Species and Geographic Patterns of Their Potential Impacts

Diseases and insects, particularly those that are non-native and invasive, arguably pose the most destructive threat to North American forests. Currently, both exotic and native insects and diseases are producing extensive ecological damage and economic impacts. As part of an effort to identify United States tree species and forests most vulnerable to these epidemics, we compiled a list of the most serious insect and disease threats for 419 native tree species and assigned a severity rating for each of the 1378 combinations between mature tree hosts and 339 distinct insect and disease agents. We then joined this list with data from a spatially unbiased and nationally consistent forest inventory to assess the potential ecological impacts of insect and disease infestations. Specifically, potential host species mortality for each host/agent combination was used to weight species importance values on approximately 132,000 Forest Inventory and Analysis (FIA) plots across the conterminous 48 United States. When summed on each plot, these weighted importance values represent an estimate of the proportion of the plot’s existing importance value at risk of being lost. These plot estimates were then used to identify statistically significant geographic hotspots and coldspots and of potential forest impacts associated with insects and diseases in total, and for different agent types. In general, the potential impacts of insects and diseases were greater in the West, where there are both fewer agents and less diverse forests. The impact of non-native invasive agents, however, was potentially greater in the East. Indeed, the impacts of current exotic pests could be greatly magnified across much of the Eastern United States if these agents are able to reach the entirety of their hosts’ ranges. Both the list of agent/host severities and the spatially explicit results can inform species-level vulnerability assessments and broad-scale forest sustainability reporting efforts, and should provide valuable information for decision-makers who need to determine which tree species and locations to target for monitoring efforts and pro-active management activities.

A new baseline for countrywide α-diversity and species distributions: illustration using >6,000 plant species in Panama

Estimating α-diversity and species distributions provides baseline information to understand factors such as biodiversity loss and erosion of ecosystem services. Yet, species surveys typically cover a small portion of any country's landmass. Public, global databases could help, but contain biases. Thus, the magnitude of bias should be identified and ameliorated, the value of integration determined, and application to current policy issues illustrated. The ideal integrative approach should be powerful, flexible, efficient, and conceptually straightforward. We estimated distributions for >6,000 species, integrating species sightings (S) from the Global Biodiversity Information Facility (GBIF), systematic survey data (S₂ ), and "bias-adjustment kernels" (BaK) using spatial and species trait databases (S₂ BaK). We validated our approach using both locational and species holdout sets, and then applied our predictive model to Panama. Using sightings alone (the most common approach) discriminated relative probabilities of occurrences well (area under the curve [AUC] = 0.88), but underestimated actual probabilities by ~4,000%, while using survey data alone omitted over three-quarters of the >6,000 species. Comparatively, S₂ BaK had no systematic underestimation, and substantially stronger discrimination (AUC = 0.96) and predictive power (deviance explained = 47%). Our model suggested high diversity (~200% countrywide mean) where urban development is projected to occur (the Panama Canal watershed) and also suggested this is not due to higher sampling intensity. However, portions of the Caribbean coast and eastern Panama (the Darién Gap) were even higher, both for total plant biodiversity (~250% countrywide mean), and CITES listed species. Finally, indigenous territories appeared half as diverse as other regions, based on survey observations. However, our model suggested this was largely due to site selection, and that richness in and out of indigenous territories was roughly equal. In brief, we provide arguably the best estimate of countrywide plant α-diversity and species distributions in the Neotropics, and make >6,000 species distributions available. We identify regions of overlap between development and high biodiversity, and improve interpretation of biodiversity patterns, including for policy-relevant CITES species, and locations with limited access (i.e., indigenous territories). We derive a powerful, flexible, efficient and simple estimation approach for biodiversity science.

Tree diversity regulates forest pest invasion

Nonnative pests often cause cascading ecological impacts, leading to detrimental socioeconomic consequences; however, how plant diversity may influence insect and disease invasions remains unclear. High species diversity in host communities may promote pest invasions by providing more niches (i.e., facilitation), but it can also diminish invasion success because low host dominance may make it more difficult for pests to establish (i.e., dilution). Most studies to date have focused on small-scale, experimental, or individual pest/disease species, while large-scale empirical studies, especially in natural ecosystems, are extremely rare. Using subcontinental-level data, we examined the role of tree diversity on pest invasion across the conterminous United States and found that the tree-pest diversity relationships are hump-shaped. Pest diversity increases with tree diversity at low tree diversity (because of facilitation or amplification) and is reduced at higher tree diversity (as a result of dilution). Thus, tree diversity likely regulates forest pest invasion through both facilitation and dilution that operate simultaneously, but their relative strengths vary with overall diversity. Our findings suggest the role of native species diversity in regulating nonnative pest invasions.

Invasive alien pests threaten the carbon stored in Europe's forests

Forests mitigate climate change by sequestering large amounts of carbon (C). However, forest C storage is not permanent, and large pulses of tree mortality can thwart climate mitigation efforts. Forest pests are increasingly redistributed around the globe. Yet, the potential future impact of invasive alien pests on the forest C cycle remains uncertain. Here we show that large parts of Europe could be invaded by five detrimental alien pests already under current climate. Climate change increases the potential range of alien pests particularly in Northern and Eastern Europe. We estimate the live C at risk from a potential future invasion as 1027 Tg C (10% of the European total), with a C recovery time of 34 years. We show that the impact of introduced pests could be as severe as the current natural disturbance regime in Europe, calling for increased efforts to halt the introduction and spread of invasive alien species.

Invasive alien pests can cause large-scale forest mortality and release carbon stored in forests. Here the authors show that climate change increases the potential range of alien pests and that their impact on the carbon cycle could be as severe as the current natural disturbance regime in Europe’s forests.

A safety rule approach to surveillance and eradication of biological invasions

Uncertainty about future spread of invasive organisms hinders planning of effective response measures. We present a two-stage scenario optimization model that accounts for uncertainty about the spread of an invader, and determines survey and eradication strategies that minimize the expected program cost subject to a safety rule for eradication success. The safety rule includes a risk standard for the desired probability of eradication in each invasion scenario. Because the risk standard may not be attainable in every scenario, the safety rule defines a minimum proportion of scenarios with successful eradication. We apply the model to the problem of allocating resources to survey and eradicate the Asian longhorned beetle (ALB, Anoplophora glabripennis) after its discovery in the Greater Toronto Area, Ontario, Canada. We use historical data on ALB spread to generate a set of plausible invasion scenarios that characterizes the uncertainty of the beetle's extent. We use these scenarios in the model to find survey and tree removal strategies that minimize the expected program cost while satisfying the safety rule. We also identify strategies that reduce the risk of very high program costs. Our results reveal two alternative strategies: (i) delimiting surveys and subsequent tree removal based on the surveys' outcomes, or (ii) preventive host tree removal without referring to delimiting surveys. The second strategy is more likely to meet the stated objectives when the capacity to detect an invader is low or the aspirations to eradicate it are high. Our results provide practical guidelines to identify the best management strategy given aspirational targets for eradication and spending.