Invasions Toolkit

Exploring the uptake of advanced digital technologies in environmental assessment practice - Experiences from Austria and Germany

Environmental assessment (EA) evaluates the environmental impacts of proposed projects, plans or policies to inform decision making. While several studies have highlighted the potential and opportunities of digitalisation for EA, few have explored practitioners' perceptions using a mixed methods approach in order to discover concerns and risks identified by EA of novel technological approaches. In addition, this initial exploratory study examines the perception of benefits and contributions to quality and effectiveness of advanced digital approaches, such as the introduction of artificial intelligence, in EA practice. The research process was based on focus group discussions and exploratory interviews with EA consultants, environmental authorities, researchers, environmental associations and NGOs. Relevant technologies were identified from the existing scientific literature and their applicability, benefits and use were discussed in context of real-world experience made by the practitioner. It became evident that the majority of practitioners in the field of EA in Austria and Germany are not familiar with advanced digital approaches and tools. While other planning disciplines are exploiting the potential of advanced digital tools, EA practitioners still share concerns about data quality, security, legal uncertainties, but also skills and know-how. The study identifies a gap and a need for training and confidence building. It aims to contribute to the promotion of inter- & transdisciplinary exchange involving the wider EA community.

Citizen science is a vital partnership for invasive alien species management and research

Invasive alien species (IAS) adversely impact biodiversity, ecosystem functions, and socio-economics. Citizen science can be an effective tool for IAS surveillance, management, and research, providing large datasets over wide spatial extents and long time periods, with public participants generating knowledge that supports action. We demonstrate how citizen science has contributed knowledge across the biological invasion process, especially for early detection and distribution mapping. However, we recommend that citizen science could be used more for assessing impacts and evaluating the success of IAS management. Citizen science does have limitations, and we explore solutions to two key challenges: ensuring data accuracy and dealing with uneven spatial coverage of potential recorders (which limits the dataset's "fit for purpose"). Greater co-development of citizen science with public stakeholders will help us better realize its potential across the biological invasion process and across ecosystems globally while meeting the needs of participants, local communities, scientists, and decision-makers.

Arthropod food webs predicted from body size ratios are improved by incorporating prey defensive properties

Trophic interactions are often deduced from body size differences, assuming that predators prefer prey smaller than themselves because larger prey are more difficult to subdue. This has mainly been confirmed in aquatic ecosystems, but rarely in terrestrial ecosystems, especially in arthropods. Our goal was to validate whether body size ratios can predict trophic interactions in a terrestrial, plant-associated arthropod community and whether predator hunting strategy and prey taxonomy could explain additional variation. We conducted feeding trials with arthropods from marram grass in coastal dunes to test whether two individuals, of the same or different species, would predate each other. From the trial results, we constructed one of the most complete, empirically derived food webs for terrestrial arthropods associated with a single plant species. We contrasted this empirical food web with a theoretical web based on body size ratios, activity period, microhabitat, and expert knowledge. In our feeding trials, predator-prey interactions were indeed largely size-based. Moreover, the theoretical and empirically based food webs converged well for both predator and prey species. However, predator hunting strategy, and especially prey taxonomy improved predictions of predation. Well-defended taxa, such as hard-bodied beetles, were less frequently consumed than expected based on their body size. For instance, a beetle of average size (measuring 4 mm) is 38% less vulnerable than another average arthropod with the same length. Body size ratios predict trophic interactions among plant-associated arthropods fairly well. However, traits such as hunting strategy and anti-predator defences can explain why certain trophic interactions do not adhere to size-based rules. Feeding trials can generate insights into multiple traits underlying real-life trophic interactions among arthropods.

Human-mediated dispersal drives the spread of the spotted lanternfly (Lycorma delicatula)

The spotted lanternfly (Lycorma delicatula) is a novel invasive insect from Asia now established and spreading throughout the United States. This species is of particular concern given its ability to decimate important crops such as grapes, fruit trees, as well as native hardwood trees. Since its initial detection in Berks County, Pennsylvania in 2014, spotted lanternfly infestations have been detected in 130 counties (87 under quarantine) within Connecticut, Delaware, Indiana, Maryland, New Jersey, New York, Ohio, Virginia, and West Virginia. Compounding this invasion is the associated proliferation and widespread distribution of the spotted lanternfly's preferred host plant, the tree-of-heaven (Ailanthus altissima). While alternate host plant species have been observed, the tree-of-heaven which thrives in disturbed and human-dominated areas (e.g., along roads and railways) is likely facilitating the population growth rates of spotted lanternfly. We simulated the population and spread dynamics of the spotted lanternfly throughout the mid-Atlantic USA to help determine areas of risk and inform continued monitoring and control efforts. We tested the prediction that spotted lanternfly spread is driven by human-mediated dispersal using agent-based models that incorporated information on its life-history traits, habitat suitability, and movement and natural dispersal behavior. Overwhelmingly, our results suggest that human-mediated dispersal (e.g., cars, trucks, and trains) is driving the observed spread dynamics and distribution of the spotted lanternfly throughout the eastern USA. Our findings should encourage future surveys to focus on human-mediated dispersal of egg masses and adult spotted lanternflies (e.g., attachment to car or transported substrates) to better monitor and control this economically and ecologically important invasive species.

Genomics reveals the history of a complex plant invasion and improves the management of a biological invasion from the South African-Australian biotic exchange

Many plants exchanged in the global redistribution of species in the last 200 years, particularly between South Africa and Australia, have become threatening invasive species in their introduced range. Refining our understanding of the genetic diversity and population structure of native and alien populations, introduction pathways, propagule pressure, naturalization, and initial spread, can transform the effectiveness of management and prevention of further introductions. We used 20,221 single nucleotide polymorphisms to reconstruct the invasion of a coastal shrub, Chrysanthemoides monilifera ssp. rotundata (bitou bush) from South Africa, into eastern Australia (EAU), and Western Australia (WAU). We determined genetic diversity and population structure across the native and introduced ranges and compared hypothesized invasion scenarios using Bayesian modeling. We detected considerable genetic structure in the native range, as well as differentiation between populations in the native and introduced range. Phylogenetic analysis showed the introduced samples to be most closely related to the southern‐most native populations, although Bayesian analysis inferred introduction from a ghost population. We detected strong genetic bottlenecks during the founding of both the EAU and WAU populations. It is likely that the WAU population was introduced from EAU, possibly involving an unsampled ghost population. The number of private alleles and polymorphic SNPs successively decreased from South Africa to EAU to WAU, although heterozygosity remained high. That bitou bush remains an invasion threat in EAU, despite reduced genetic diversity, provides a cautionary biosecurity message regarding the risk of introduction of potentially invasive species via shipping routes.

A review of invasive species reporting apps for citizen science and opportunities for innovation

Smartphone apps have enhanced the potential for monitoring of invasive alien species (IAS) through citizen science. They now have the capacity to massively increase the volume and spatiotemporal coverage of IAS occurrence data accrued in centralised databases. While more reporting apps are developed each year, innovation across diverse functionalities and data management in this field are occurring separately and simultaneously amongst numerous research groups with little attention to trends, priorities and opportunities for improvement. This creates the risk of duplication of effort and missed opportunities for implementing new and existing functionalities that would directly benefit IAS research and management. Using a literature search of Early Detection and Rapid Response implementation, smartphone app development and invasive species reporting apps, we developed a rubric for quantitatively assessing the functionality of IAS reporting apps and applied this rubric to 41 free, English-language IAS reporting apps, available via major mobile app stores in North America. The five highest performing apps achieved scores of 61.90% to 66.35% relative to a hypothetical maximum score, indicating that many app features and functionalities, acknowledged to be useful for IAS reporting in literature, are not present in sampled apps. This suggests that current IAS reporting apps do not make use of all available and known functionalities that could maximise their efficacy. Major implementation gaps, highlighted by this rubric analysis, included limited implementation in user engagement (particularly gamification elements and social media compatibility), ancillary information on search effort, detection method, the ability to report absences and local habitat characteristics. The greatest advancement in IAS early detection would likely result from app gamification. This would make IAS reporting more engaging for a growing community of non-professional contributors and encourage frequent and prolonged participation. We discuss these implementation gaps in relation to the increasingly urgent need for Early Detection and Rapid Response frameworks. We also recommend future innovations in IAS reporting app development to help slow the spread of IAS and curb the global economic and biodiversity extinction crises. We also suggest that further funding and investment in this and other implementation gaps could greatly increase the efficacy of current IAS reporting apps and increase their contributions to addressing the contemporary biological invasion threat.

The Rapid Rise of Next-Generation Natural History

Many ecologists have lamented the demise of natural history and have attributed this decline to a misguided view that natural history is outdated and unscientific. Although there is a perception that the focus in ecology and conservation have shifted away from descriptive natural history research and training toward hypothetico-deductive research, we argue that natural history has entered a new phase that we call “next-generation natural history.” This renaissance of natural history is characterized by technological and statistical advances that aid in collecting detailed observations systematically over broad spatial and temporal extents. The technological advances that have increased exponentially in the last decade include electronic sensors such as camera-traps and acoustic recorders, aircraft- and satellite-based remote sensing, animal-borne biologgers, genetics and genomics methods, and community science programs. Advances in statistics and computation have aided in analyzing a growing quantity of observations to reveal patterns in nature. These robust next-generation natural history datasets have transformed the anecdotal perception of natural history observations into systematically collected observations that collectively constitute the foundation for hypothetico-deductive research and can be leveraged and applied to conservation and management. These advances are encouraging scientists to conduct and embrace detailed descriptions of nature that remain a critically important component of the scientific endeavor. Finally, these next-generation natural history observations are engaging scientists and non-scientists alike with new documentations of the wonders of nature. Thus, we celebrate next-generation natural history for encouraging people to experience nature directly.

Evidence for Range Expansion and Origins of an Invasive Hornet Vespa bicolor (Hymenoptera, Vespidae) in Taiwan, with Notes on Its Natural Status

Simple Summary

The invasive hornet Vespa bicolor Fabricius was first discovered in Taiwan in 2003 and was not confirmed to have been established until 2014. This study was conducted in order to (1) assess the current status of V. bicolor abundance, dispersal, seasonality, and possible impact on honeybee (Apis mellifera Linnaeus) in Taiwan; (2) and to trace the origins of Taiwan’s V. bicolor population. To assess V. bicolor abundance, we used visual surveys, sweep netting, and hornet traps in four known ranges in northern and central Taiwan from 2016 to 2020. Additionally, to understand V. bicolor dispersion, we mapped environmental data using ArcGIS, and to predict future V. bicolor range, we used ecological niche modeling. The results show that V. bicolor has stable populations in three areas in northern and central Taiwan, and mainly preys on Apis mellifera. Our analyses suggest samples from Southeastern China as having the closest relation in DNA sequences with Taiwan’s V. bicolor population. Due to the negative economic and ecological impacts of V. bicolor in Taiwan, our findings shed light on the value of monitoring and controlling its populations, rather than working exclusively towards elimination.

Abstract

The invasive alien species (IAS) Vespa bicolor is the first reported hornet that has established in Taiwan and is concerning as they prey on honeybee Apis mellifera, which leads to colony losses and public concerns. Thus, the aim of this study was to assess the current status of V. bicolor abundance, dispersal, and impact and to trace the origins of Taiwan’s V. bicolor population. Our studies took place in five areas in northern to central Taiwan. We used mtDNA in the phylogenetic analyses. Field survey and ecological niche modeling (ENM) were used to understand the origins and current range of the invasive species. Two main subgroups of V. bicolor in the phylogenetic tree were found, and a clade with short branch lengths in Southeastern China and Taiwan formed a subgroup, which shows that the Taiwan population may have invaded from a single event. Evidence shows that V. bicolor is not a severe pest to honeybees in the study area; however, using ENM, we predict the rapid dispersion of this species to the cooler and hilly mountain areas of Taiwan. The management of V. bicolor should also involve considering it a local pest to reduce loss by beekeepers and public fear in Taiwan. Our findings highlight how the government, beekeepers, and researchers alike should be aware of the implications of V. bicolor’s rapid range expansion in Taiwan, or in other countries.

Differential immune gene expression associated with contemporary range expansion in two invasive rodents in Senegal

Biological invasions are major anthropogenic changes associated with threats to biodiversity and health. However, what determines the successful establishment and spread of introduced populations remains unclear. Here, we explore several hypotheses linking invasion success and immune phenotype traits, including those based on the evolution of increased competitive ability concept. We compared gene expression profiles between anciently and recently established populations of two major invading species, the house mouse Mus musculus domesticus and the black rat Rattus rattus, in Senegal (West Africa). Transcriptome analyses identified differential expression between anciently and recently established populations for 364 mouse genes and 83 rat genes. All immune-related genes displaying differential expression along the mouse invasion route were overexpressed at three of the four recently invaded sites studied. Complement activation pathway genes were overrepresented among these genes. By contrast, no particular immunological process was found to be overrepresented among the differentially expressed genes of black rat. Changes in transcriptome profiles were thus observed along invasion routes, but with different specific patterns between the two invasive species. These changes may be driven by increases in infection risks at sites recently invaded by the house mouse, and by stochastic events associated with colonization history for the black rat. These results constitute a first step toward the identification of immune eco-evolutionary processes potentially involved in the invasion success of these two rodent species.

A methodological framework to analyse determinants of host-microbiota networks, with an application to the relationships between Daphnia magna's gut microbiota and bacterioplankton

The past 30 years have seen both a surge of interest in assessing ecological interactions using tools borrowed from network theory and an explosion of data on the occurrence of microbial symbionts thanks to next-generation sequencing. Given that classic network methods cannot currently measure the respective effects of different environmental and biological drivers on network structure, we here present two methods to elucidate the determinants of bipartite interaction networks. The first method is based on classifications and compares communities within networks to the grouping of nodes by treatment or similar controlling groups. The second method assesses the link between multivariate explanatory variables and network structure using redundancy analyses after singular value decomposition. In both methods, the significance of effects can be gauged through two randomizations. Our methods were applied to experimental data on Daphnia magna and its interactions with gut microbiota and bacterioplankton. The whole network was affected by Daphnia's diet (algae and/or cyanobacteria) and sample type, but not by Daphnia genotype. At coarse grains, bacterioplankton and gut microbiota communities were different. At this scale, the structure of the gut microbiota-based network was not linked to any explanatory factors, while the bacterioplankton-based network was related to both Daphnia's diet and genotype. At finer grains, Daphnia's diet and genotype affected both microbial networks, but the effect of diet on gut microbiota network structure was mediated solely by differences in microbial richness. While no reciprocal effect between the microbial communities could be found, fine-grained analyses presented a more nuanced picture, with bacterioplankton likely affecting the composition of the gut microbiota. Our methods are widely applicable to bipartite networks, can elucidate both controlled and environmental effects in experimental setting using a large amount of sequencing data and can tease apart reciprocal effects of networks on one another. The twofold approach we propose has the advantage of being able to tease apart effects at different scales of network structure, thus allowing for detailed assessment of reciprocal effects of linked networks on one another. As such, our network methods can help ecologists understand huge datasets reporting microbial co-occurrences within different hosts.

Evaluating the Effect of Prosopis juliflora, an Alien Invasive Species, on Land Cover Change Using Remote Sensing Approach

Invasive plant species (IPS) affect people’s livelihoods and well-being by providing both benefits and costs in different contexts. The objective of this study was to investigate the impact of Prosopis juliflora invasion on land cover change using ground survey and satellite sensor data derived from Landsat ETM+. The study was conducted at Sweimeh, Jordan Valley, between 1999 and 2017. The overall classification accuracy of remotely sensed data was 86% for 1999 and 80% for 2017. Accordingly, a remote sensing approach has the potential to assess land change/cover and aid in monitoring the IPS, specifically Prosopis invasion. Change detection analysis of Landsat classes (i.e., 1999 and 2017) showed that bare soil, urban, and water surface areas decreased by 6%, 11%, and 3%, respectively. Conversely, the vegetation class (i.e., IPS and native plants) increased by 20%. Ground surveys in 1999 and 2017 showed that the average vegetation area in Sweimeh invaded by Prosopis was approximately 60% in 1999 and 70% in 2017. Accordingly, the total estimated area invaded by P. juliflora at Sweimeh (2106 ha) in 1999 was approximately 92 ha, while Prosopis coverage in the same region was approximately 413 ha in 2017. The high emergence rate, the adaptation to high temperatures and low precipitation as well as governmental regulations which restrict the removal of trees, including IPS, were the main factors that prompted the extreme P. juliflora invasion in the Jordan Valley. The high invasion rate has led to a reduction in native species, including Tamarix spp., and dried up five natural water springs in the area. Overall, a monitoring plan should be applied to control the invasion problem by Prosopis in the valley. In addition, the conservation regulations that deal with IPS should be revised to mitigate the IPS risk.

Genomic biosurveillance of forest invasive alien enemies: A story written in code

The world's forests face unprecedented threats from invasive insects and pathogens that can cause large irreversible damage to the ecosystems. This threatens the world's capacity to provide long-term fiber supply and ecosystem services that range from carbon storage, nutrient cycling, and water and air purification, to soil preservation and maintenance of wildlife habitat. Reducing the threat of forest invasive alien species requires vigilant biosurveillance, the process of gathering, integrating, interpreting, and communicating essential information about pest and pathogen threats to achieve early detection and warning and to enable better decision-making. This process is challenging due to the diversity of invasive pests and pathogens that need to be identified, the diverse pathways of introduction, and the difficulty in assessing the risk of establishment. Genomics can provide powerful new solutions to biosurveillance. The process of invasion is a story written in four chapters: transport, introduction, establishment, and spread. The series of processes that lead to a successful invasion can leave behind a DNA signature that tells the story of an invasion. This signature can help us understand the dynamic, multistep process of invasion and inform management of current and future introductions. This review describes current and future application of genomic tools and pipelines that will provide accurate identification of pests and pathogens, assign outbreak or survey samples to putative sources to identify pathways of spread, and assess risk based on traits that impact the outbreak outcome.

Technology innovation: advancing capacities for the early detection of and rapid response to invasive species

The 2016–2018National Invasive Species Council (NISC) Management Plan and Executive Order 13751 call for US federal agencies to foster technology development and application to address invasive species and their impacts. This paper complements and draws on an Innovation Summit, review of advanced biotechnologies applicable to invasive species management, and a survey of federal agencies that respond to these high-level directives. We provide an assessment of federal government capacities for the early detection of and rapid response to invasive species (EDRR) through advances in technology application; examples of emerging technologies for the detection, identification, reporting, and response to invasive species; and guidance for fostering further advancements in applicable technologies. Throughout the paper, we provide examples of how federal agencies are applying technologies to improve programmatic effectiveness and cost-efficiencies. We also highlight the outstanding technology-related needs identified by federal agencies to overcome barriers to enacting EDRR. Examples include improvements in research facility infrastructure, data mobilization across a wide range of invasive species parameters (from genetic to landscape scales), promotion of and support for filling key gaps in technological capacity (e.g., portable, field-ready devices with automated capacities), and greater investments in technology prizes and challenge competitions.

The early detection of and rapid response (EDRR) to invasive species: a conceptual framework and federal capacities assessment

Globalization necessitates that we address the negative externalities of international trade and transport, including biological invasion. The US government defines invasive species to mean, “with regard to a particular ecosystem, a non-native organism whose introduction causes, or is likely to cause, economic or environmental harm, or harm to human, animal, or plant health.” Here we address the role of early detection of and rapid response to invasive species (EDRR) in minimizing the impact of invasive species on US interests. We provide a review of EDRR’s usage as a federal policy and planning term, introduce a new conceptual framework for EDRR, and assess US federal capacities for enacting well-coordinated EDRR. Developing a national EDRR program is a worthwhile goal; our assessment nonetheless indicates that the federal government and its partners need to overcome substantial conceptual, institutional, and operational challenges that include establishing clear and consistent terminology use, strategically identifying and communicating agency functions, improving interagency budgeting, facilitating the application of emerging technologies and other resources to support EDRR, and making information relevant to EDRR preparedness and implementation more readily accessible. This paper is the first in a special issue of Biological Invasions that includes 12 complementary papers intended to inform the development and implementation of a national EDRR program.

Right place. Right time. Right tool: guidance for using target analysis to increase the likelihood of invasive species detection

In response to the National Invasive Species Council’s 2016–2018 Management Plan, this paper provides guidance on applying target analysis as part of a comprehensive framework for the early detection of and rapid response to invasive species (EDRR). Target analysis is a strategic approach for detecting one or more invasive species at a specific locality and time, using a particular method and/or technology(ies). Target analyses, which are employed across a wide range of disciplines, are intended to increase the likelihood of detection of a known target in order to maximize survey effectiveness and cost-efficiency. Although target analyses are not yet a standard approach to invasive species management, some federal agencies are employing target analyses in principle and/or in part to improve EDRR capacities. These initiatives can provide a foundation for a more standardized and comprehensive approach to target analyses. Guidance is provided for improving computational information. Federal agencies and their partners would benefit from a concerted effort to collect the information necessary to perform rigorous target analyses and make it available through open access platforms.

Diet assessment of two land planarian species using high-throughput sequencing data

Geoplanidae (Platyhelminthes: Tricladida) feed on soil invertebrates. Observations of their predatory behavior in nature are scarce, and most of the information has been obtained from food preference experiments. Although these experiments are based on a wide variety of prey, this catalog is often far from being representative of the fauna present in the natural habitat of planarians. As some geoplanid species have recently become invasive, obtaining accurate knowledge about their feeding habits is crucial for the development of plans to control and prevent their expansion. Using high throughput sequencing data, we perform a metagenomic analysis to identify the in situ diet of two endemic and codistributed species of geoplanids from the Brazilian Atlantic Forest: Imbira marcusi and Cephaloflexa bergi. We have tested four different methods of taxonomic assignment and find that phylogenetic-based assignment methods outperform those based on similarity. The results show that the diet of I. marcusi is restricted to earthworms, whereas C. bergi preys on spiders, harvestmen, woodlice, grasshoppers, Hymenoptera, Lepidoptera and possibly other geoplanids. Furthermore, both species change their feeding habits among the different sample locations. In conclusion, the integration of metagenomics with phylogenetics should be considered when establishing studies on the feeding habits of invertebrates.

A Comparison of Machine-Learning Methods to Select Socioeconomic Indicators in Cultural Landscapes

Cultural landscapes are regarded to be complex socioecological systems that originated as a result of the interaction between humanity and nature across time. Cultural landscapes present complex-system properties, including nonlinear dynamics among their components. There is a close relationship between socioeconomy and landscape in cultural landscapes, so that changes in the socioeconomic dynamic have an effect on the structure and functionality of the landscape. Several numerical analyses have been carried out to study this relationship, with linear regression models being widely used. However, cultural landscapes comprise a considerable amount of elements and processes, whose interactions might not be properly captured by a linear model. In recent years, machine-learning techniques have increasingly been applied to the field of ecology to solve regression tasks. These techniques provide sound methods and algorithms for dealing with complex systems under uncertainty. The term ‘machine learning’ includes a wide variety of methods to learn models from data. In this paper, we study the relationship between socioeconomy and cultural landscape (in Andalusia, Spain) at two different spatial scales aiming at comparing different regression models from a predictive-accuracy point of view, including model trees and neural or Bayesian networks.

Range expansion of the Asian native giant resin bee Megachile sculpturalis (Hymenoptera, Apoidea, Megachilidae) in France

In 2008, a new species for the French bee fauna was recorded in Allauch near Marseille: the giant resin bee, Megachile sculpturalis (Smith, 1853). This was the first European record of this species that is native to East Asia. To our knowledge, it is the first introduced bee species in Europe. Here, we provide an overview of the current distribution of M. sculpturalis in France and we describe the history of its range expansion. Besides our own observations, information was compiled from literature and Internet websites, and by contacting naturalist networks. We collected a total of 117 records (locality × year combinations) for the 2008-2016 period. The geographical range of M. sculpturalis has extended remarkably, now occupying a third of continental France, with the most northern and western records located 335 and 520 km from Allauch, respectively. Information on its phenology, feeding, and nesting behavior is also provided. We report several events of nest occupation or eviction of Osmia sp. and Xylocopa sp. individuals by M. sculpturalis. Our results show that M. sculpturalis is now well established in France. Given its capacity to adapt and rapidly expand its range, we recommend amplifying the monitoring of this species to better anticipate the changes in its geographical range and its potential impacts on native bees.