Designing efficient surveys: spatial arrangement of sample points for detection of invasive species

An acoustic-based method for locating maternity colonies of rare woodland bats

Locating colonies of rare bats can be a time consuming process, as it is often difficult to know where to focus survey effort. However, identifying peaks of bat activity via acoustic monitoring may provide insights into whether a colony is locally present, and help screen out sites with low potential. Using a triage approach, we developed a survey methodology for locating colonies of the woodland-specialist barbastelle bat (Barbastella barbastellus). We investigated whether woodland occupancy by a colony could be predicted by acoustic data, and assessed the influence of survey effort (number of acoustic detectors deployed) on detectability. The methodology was then trialled in citizen science surveys of 77 woodlands, with follow-up radio-tracking surveys by specialists being used to confirm presence or absence. Using Receiver Operating Characteristic (ROC) curve analysis, we found that a threshold of four barbastelle passes recorded by at least one detector within one hour of sunset optimised the balance between the true- and false-positive rates. Subsequently, we found that a minimum survey effort of one detector per 6.25 hectares of woodland was needed to ensure a colony would be detected using this threshold, based on a survey sensitivity of 90%. Radio-tracking surveys in a subset of the woodlands, identified as having a high probability of being occupied by a colony based on acoustic monitoring, confirmed the presence of five previously unknown barbastelle maternity colonies. These results demonstrate that a triage system, in which high probability woodland sites are identified based on acoustic survey data, can be used to prioritise sites for future specialist surveys and conservation action.

Non-destructive insect metabarcoding for surveillance and biosecurity in citrus orchards: recording the good, the bad and the psyllids

Background

The Australian citrus industry remains one of the few in the world to be unaffected by the African and the Asian citrus psyllids, Trioza erytreae Del Guercio and Diaphorina citri Kuwayama, respectively, and the diseases their vectored bacteria can cause. Surveillance, early detection, and strict quarantine measures are therefore fundamental to safeguard Australian citrus. However, long-term targeted surveillance for exotic citrus pests can be a time-consuming and expensive activity, often relying on manually screening large numbers of trap samples and morphological identification of specimens, which requires a high level of taxonomic knowledge.

Methods

Here we evaluated the use of non-destructive insect metabarcoding for exotic pest surveillance in citrus orchards. We conducted an 11-week field trial, between the months of December and February, at a horticultural research farm (SuniTAFE Smart Farm) in the Northwest of Victoria, Australia, and processed more than 250 samples collected from three types of invertebrate traps across four sites.

Results

The whole-community metabarcoding data enabled comparisons between different trapping methods, demonstrated the spatial variation of insect diversity across the same orchard, and highlighted how comprehensive assessment of insect biodiversity requires use of multiple complimentary trapping methods. In addition to revealing the diversity of native psyllid species in citrus orchards, the non-targeted metabarcoding approach identified a diversity of other pest and beneficial insects and arachnids within the trap bycatch, and recorded the presence of the triozid Casuarinicola cf warrigalensis for the first time in Victoria. Ultimately, this work highlights how a non-targeted surveillance approach for insect monitoring coupled with non-destructive DNA metabarcoding can provide accurate and high-throughput species identification for biosecurity and biodiversity monitoring.

Simulation to investigate site-based monitoring of pest insect species for trade

Pest insect surveillance using lures is widely used to support market access requirements for traded articles that are hosts or carriers of quarantine pests. Modeling has been used extensively to guide the design of surveillance to support pest free area claims but is less commonly applied to provide confidence in pest freedom or low pest prevalence within sites registered for trade. Site-based surveillance typically needs to detect pests that are already present in the site or that may be entering the site from surrounding areas. We assessed the ability of site-based surveillance strategies to detect pests originating from within or outside the registered site using a probabilistic trapping network simulation model with random-walk insect movement and biologically realistic parameters. For a given release size, time-dependent detection probability was primarily determined by trap density and lure attractiveness, whereas mean step size (daily dispersal) had limited effect. Results were robust to site shape and size. For pests already within the site, detection was most sensitive using regularly spaced traps. Perimeter traps performed best for detecting pests moving into the site, although the importance of trap arrangement decreased with time from release, and random trap placement performed relatively well compared to regularly spaced traps. High detection probabilities were achievable within 7 days using realistic values for lure attractiveness and trap density. These findings, together with the modeling approach, can guide the development of internationally agreed principles for designing site-based surveillance of lure-attractant pests that is calibrated against the risk of non-detection.

Transect-based trapping for area-wide delimitation of insects

Typical delimitation trapping survey designs for area-wide (nonlocalized) insect populations are regularly spaced grids, and alternative shapes have not been evaluated. We hypothesized that transect-based designs could give similar detection rates with significantly shorter servicing distances. We used the TrapGrid model to investigate novel "trap-sect" designs incorporating crossed, spoked, and parallel lines of traps, comparing them to a regular grid, in single survey and multiple-site scenarios. We calculated minimum servicing distances and simulated mean probabilities of detecting a pest population, judging overall performance of trap network designs using both metrics. For single sites, trap-sect designs reduced service distances by 65-89%, and most had similar detection probabilities as the regular grid. Kernel-smoothed intensity plots indicated that the best performing trap-sect designs distributed traps more fully across the area. With multiple sites (3 side by side), results depended on insect dispersal ability. All designs performed similarly in terms of detection for highly mobile insects, suggesting that designs minimizing service distances would be best for such pests. For less mobile pests the best trap-sect designs had 4-6 parallel lines, or 8 spokes, which reduced servicing distances by 33-50%. Comparisons of hypothetical trap-sect arrays to real program trap locations for 2 pests demonstrated that the novel designs reduced both trap numbers and service distances, with little differences in mean nearest trap distance to random pest locations. Trap-sect designs in delimitation surveys could reduce costs and increase program flexibility without harming the ability to detect populations.

The Gulf Coast Tick, Amblyomma maculatum (Ixodida: Ixodidae), and Spotted Fever Group Rickettsia in the Highly Urbanized Northeastern United States

We report the multi-year collection of the Gulf Coast tick, Amblyomma maculatum Koch (Acaridae: Ixodida: Ixodidae) in Staten Island, New York City (NYC) as well as their detection in Brooklyn, NYC, and in Atlantic and Cumberland counties in southern New Jersey, USA. The first and most common detections were of adults, however in Freshkills Park on Staten Island larvae were also collected in a following year. The presence of larvae indicates that adults are successfully finding hosts in Staten Island. While it is still unknown how A. americanum reached Staten Island, immatures of this species often parasitize migratory birds, which are now often seen in Freshkills Park. We describe the landscape features of the area in Staten Island where populations were highest and larvae were detected, which could have facilitated the establishment of A. maculatum. Notably, we also report the presence of human pathogens Rickettsia parkeri in 5/10 (50%) of adults tested and R. felis in 1/24 (4.17%) of larvae tested. In addition to established populations in Staten Island we found evidence of A. maculatum in NJ and other NYC boroughs, suggesting current or future establishment is possible. The failure thus far to detect established populations in these areas may be due to inherent difficulties in detecting low density, spatially heterogeneous incipient populations, which could require targeted surveillance efforts for this species. We discuss the consequences to public health of the establishment of A. maculatum and detection of two additional rickettsial pathogens in the densely populated northeastern United States.

Simulation-based evaluation of two insect trapping grids for delimitation surveys

In the United States of America, delimitation trapping surveys with square grids have been used for decades for exotic insects without rigorous evaluation. We used simulations to investigate the effectiveness of two representative designs: an 8-km grid for Acrolepiopsis assectella (leek moth) and a 14.5-km grid for Ceratitis capitata (Mediterranean fruit fly, "Medfly"). We investigated grid compositions and design factors, measuring performance as the mean probability of pest capture over all traps, p(capture), and designed improved grids for both species. For the standard designs, p(capture) was 0.86 for leek moth and 0.71 for Medfly, with the latter performing better due to greater lure and trap attractiveness. For both designs, 86 percent or more of mean p(capture) came from core area captures. Egress testing indicated that both grids were oversized. An improved grid for leek moths would use 177 traps in a 4.8-km diameter circle, which had mean p(capture) = 0.73 and reduced the cost by 80 percent. The best Medfly grid was a 4.8-km diameter circle with 232 traps, which gave mean p(capture) of 0.66 and reduced the cost by 86 percent. Simulation may be used to improve trapping survey plans, often saving significantly on costs while maintaining survey performance.

Horizon scanning for prioritising invasive alien species with potential to threaten agriculture and biodiversity in Ghana

Invasive alien species (IAS) continue to shape the global landscape through their effects on biological diversity and agricultural productivity. The effects are particularly pronounced in Sub-Saharan Africa, which has seen the arrival of many IAS in recent years. This has been attributed to porous borders, weak cross border biosecurity, and inadequate capacity to limit or stop invasions. Prediction and early detection of IAS, as well as mechanisms of containment and eradication, are needed in the fight against this global threat. Horizon scanning is an approach that enables gathering of information on risk and impact that can support IAS management. A study was conducted in Ghana to establish two ranked lists of potential invasive alien plant pest species that could be harmful to agriculture, forestry, and the environment, and to rank them according to their potential threat. The ultimate objective was to enable prioritization of actions including pest risk analysis, prevention, surveillance and contingency plans. Prioritisation was carried out using an adapted version of horizon scanning and consensus methods developed for ranking IAS worldwide. Following a horizon scan of invasive alien species not yet officially present in Ghana, a total of 110 arthropod and 64 pathogenic species were assessed through a simplified pest risk assessment. Sixteen species, of which 14 were arthropods and two pathogens, had not been recorded on the African continent at the time of assessment. The species recorded in Africa included 19 arthropod and 46 pathogenic species which were already recorded in the neighbouring countries of Burkina Faso, Côte d’Ivoire, and Togo. The majority of arthropod species were likely to arrive as contaminants on commodities, followed by a sizable number which were likely to arrive as stowaways, while some species were capable of long distance dispersal unaided. The main actions suggested for species that scored highly included full pest risk analyses and, for species recorded in neighbouring countries, surveys to determine their presence in Ghana were recommended.

Simulation-Based Investigation of the Performance of Delimiting Trapping Surveys for Insect Pests

Fully trapped survey designs are widely used to delimit adventive pests populations that can be detected using traps and lures. Delimitation includes verifying the presence of the pest and determining its spatial extent. The size and shape of the survey design and the density of traps can vary; however, resulting variation in detecting efficiency is often unknown. We used a trapping network simulation model with diffusion-based insect movement to investigate delimiting survey trapping design performance for fully trapped and some modified designs. Simulations included randomized outbreak locations in a core area and a duration of 30 d. We assessed impacts of insect dispersal ability, grid size and shape, and trap attractiveness and density on survey performance, measured as mean probability of capturing individual pests [p(capture)]. Most published grids are square, but circles performed equally well and are more efficient. Over different grid sizes, p(capture) increased for insects with greater dispersal ability but was generally unresponsive to size because most captures occurred in central areas. For low dispersing insects, the likelihood of egress was approximately zero with a 3.2-km square grid, whereas an 11.3-km grid was needed to contain highly vagile insects. Trap attractiveness affected p(capture) more strongly than density: lower densities of poorly attractive traps may underperform expectations. Variable density designs demonstrated potential for cost savings but highlighted that resource-intensive outer bands are critical to boundary determination. Results suggesting that many grids are oversized need empirical verification, whereas other principles, such as using circular shapes, are readily adoptable now.

Ground and Stem Sampling as Potential Detection Tools for the Wool of Adelges tsugae (Hemiptera: Adelgidae)

The wool of the invasive, non-native hemlock woolly adelgid, Adelges tsugae Annand (Hemiptera: Adelgidae), occurs mostly on hemlock (Tsuga sp.) twigs, but can be dislodged from the canopy and end up on the forest floor and tree stem underneath the canopy. Herein, we developed and tested the efficacy of two novel sampling techniques, which are based on a visual examination of the forest floor and the hemlock stem for A. tsugae wool. Subsequently, we compared these two techniques to a visual examination of foliage and ball sampling which are two methods currently used operationally. We sampled 11 hemlock stands, with low to moderate incidence A. tsugae populations, near Ithaca, New York in 2016 and assessed the probability of detecting wool on a tree and in a stand, as well as the relative variation and relative net precision for each of the four techniques. We found that sampling the tree stem outperformed foliage and ground sampling, likely because of its higher detection rate and lower relative variation, but not ball sampling. Our findings suggest that combining stem, ball and ground sampling was the most effective combination of techniques and gave a high probability of detecting an infested tree or an infested stand. All techniques were an improvement over foliage sampling, even after increasing the foliage sampling effort fivefold.

Quantifying Planococcus ficus (Hemiptera: Pseudococcidae) Invasion in Northern California Vineyards to Inform Management Strategy

The spread and impact of invasive species in exotic ranges can be mitigated by increased understanding of pest invasion dynamics. Here, we used geospatial analyses and habitat suitability modeling to characterize the invasion of an important vineyard pest, vine mealybug (Planococcus ficus Signoret, Hemiptera: Pseudococcidae), using nearly 15,000 trapping records from throughout Napa County, California, between 2012 and 2017. Spatial autocorrelation among P. ficus detections was strongest at distances of ~250 m and detectable at regional scales (up to 40 km), estimates of the rate and directionality of spread were highly idiosyncratic, and P. ficus detection hotspots were spatiotemporally dynamic. Generalized linear model, boosted regression tree, and random forest modeling methods performed well in predicting habitat suitability for P. ficus. The most important predictors of P. ficus occurrence were a positive effect of precipitation in the driest month, and negative effects of elevation and distance to nearest winery. Our results indicate that 250-m quarantine and treatment zones around P. ficus detections are likely sufficient to encompass most local establishment and spread, and that implementing localized regulatory procedures may limit inadvertent P. ficus spread via anthropogenic pathways. Finally, surveys of P. ficus presence at >300 vineyard sites validated that habitat suitability estimates were significantly and positively associated with P. ficus frequency of occurrence. Our findings indicate that habitat suitability predictions may offer a robust tool for identifying areas in the study region at risk to future P. ficus invasion and prioritizing locations for early detection and preventative management efforts.

Optimal invasive species surveillance in the real world: practical advances from research

When alien species make incursions into novel environments, early detection through surveillance is critical to minimizing their impacts and preserving the possibility of timely eradication. However, incipient populations can be difficult to detect, and usually, there are limited resources for surveillance or other response activities. Modern optimization techniques enable surveillance planning that accounts for the biology and expected behavior of an invasive species while exploring multiple scenarios to identify the most cost-effective options. Nevertheless, most optimization models omit some real-world limitations faced by practitioners during multi-day surveillance campaigns, such as daily working time constraints, the time and cost to access survey sites and personnel work schedules. Consequently, surveillance managers must rely on their own judgments to handle these logistical details, and default to their experience during implementation. This is sensible, but their decisions may fail to address all relevant factors and may not be cost-effective. A better planning strategy is to determine optimal routing to survey sites while accounting for common daily logistical constraints. Adding site access and other logistical constraints imposes restrictions on the scope and extent of the surveillance effort, yielding costlier but more realistic expectations of the surveillance outcomes than in a theoretical planning case.

Optimising risk-based surveillance for early detection of invasive plant pathogens

Emerging infectious diseases (EIDs) of plants continue to devastate ecosystems and livelihoods worldwide. Effective management requires surveillance to detect epidemics at an early stage. However, despite the increasing use of risk-based surveillance programs in plant health, it remains unclear how best to target surveillance resources to achieve this. We combine a spatially explicit model of pathogen entry and spread with a statistical model of detection and use a stochastic optimisation routine to identify which arrangement of surveillance sites maximises the probability of detecting an invading epidemic. Our approach reveals that it is not always optimal to target the highest-risk sites and that the optimal strategy differs depending on not only patterns of pathogen entry and spread but also the choice of detection method. That is, we find that spatial correlation in risk can make it suboptimal to focus solely on the highest-risk sites, meaning that it is best to avoid ‘putting all your eggs in one basket’. However, this depends on an interplay with other factors, such as the sensitivity of available detection methods. Using the economically important arboreal disease huanglongbing (HLB), we demonstrate how our approach leads to a significant performance gain and cost saving in comparison with conventional methods to targeted surveillance.

Emerging infectious diseases of plants continue to devastate ecosystems and livelihoods worldwide. By linking a mathematical model of pest spread with a computational optimisation routine, this study identifies where to look for invasive pests if we wish to detect them at an early stage; this method improves upon conventional methods of risk-based surveillance and is robust to model misspecification.

Sticky traps as an early detection tool for crawlers of Adelges tsugae (Hemiptera: Adelgidae)

We developed an approach using sticky trap arrays as an early detection tool for populations of first-instar nymphs of the hemlock woolly adelgid (Adelges tsugae Annand), a pest of hemlocks (Tsuga spp. [Pinaceae]) in North America. We considered the detection rate of at least one nymph from trapping arrays consisting of one to six sticky panels, where we varied both the surface area of each trap that we assessed and the length of the trapping duration. We also estimated the time needed to set up, service, and assess groups of traps and attempted to relate capture of nymphs on traps to incidence and abundance of A. tsugae in the canopy above the traps. Arrays consisting of two traps provided a detection rate of 75% when 87.5% of the surface area of each trap was assessed, a process that required 38 min per array. The probability of detecting nymphs on traps left in the field for 5-6 d was similar to that for traps left for 12 d. The number of nymphs trapped in an array predicted the probability of finding A. tsugae in the canopy but only when all six traps were fully assessed. To reliably detect incipient A. tsugae infestations, we recommend placing arrays of traps at 1 km intervals along the perimeter of a stand during peak activity of first-instar sistentes nymphs and servicing these arrays every 5-7 d.

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.

Prospects and challenges of implementing DNA metabarcoding for high-throughput insect surveillance

Trap-based surveillance strategies are widely used for monitoring of invasive insect species, aiming to detect newly arrived exotic taxa as well as track the population levels of established or endemic pests. Where these surveillance traps have low specificity and capture non-target endemic species in excess of the target pests, the need for extensive specimen sorting and identification creates a major diagnostic bottleneck. While the recent development of standardized molecular diagnostics has partly alleviated this requirement, the single specimen per reaction nature of these methods does not readily scale to the sheer number of insects trapped in surveillance programmes. Consequently, target lists are often restricted to a few high-priority pests, allowing unanticipated species to avoid detection and potentially establish populations. DNA metabarcoding has recently emerged as a method for conducting simultaneous, multi-species identification of complex mixed communities and may lend itself ideally to rapid diagnostics of bulk insect trap samples. Moreover, the high-throughput nature of recent sequencing platforms could enable the multiplexing of hundreds of diverse trap samples on a single flow cell, thereby providing the means to dramatically scale up insect surveillance in terms of both the quantity of traps that can be processed concurrently and number of pest species that can be targeted. In this review of the metabarcoding literature, we explore how DNA metabarcoding could be tailored to the detection of invasive insects in a surveillance context and highlight the unique technical and regulatory challenges that must be considered when implementing high-throughput sequencing technologies into sensitive diagnostic applications.

Effect of Lure Combination on Fruit Fly Surveillance Sensitivity

Surveillance for invading insect pests is costly and the trapper usually finds the traps empty of the target pest. Since the successful establishment of new pests is an uncommon event, multiple lures placed into one trap might increase the efficiency of the surveillance system. We investigated the effect of the combination of the Tephritidae male lures - trimedlure, cuelure, raspberry ketone and methyl eugenol - on catch of Ceratitis capitata, Zeugodacus cucurbitae, Bactrocera tryoni, B. dorsalis, B. aquilonis and B. tenuifascia in Australia and the USA (not all species are present in each country). The increase in trap density required to offset any reduction in catch due to the presence of lures for other Tephritidae was estimated. The effect of increasing trap density to maintain surveillance sensitivity was modelled for a hypothetical population of B. tryoni males, where the effective sampling area of cuelure traps for this species has been estimated. The 3-way combination significantly reduced the catch of the methyl eugenol-responsive B. dorsalis. Unexpectedly, we found that trimedlure-baited traps that contained methyl eugenol had ×3.1 lower catch of C. capitata than in trimedlure-only-baited traps in Australia, but not in Hawaii where no difference in catch was observed, we cannot satisfactorily explain this result. Based on the data presented here and from previous research, combinations of some male lures for the early detection of tephritid flies appear compatible and where there is any reduction in surveillance sensitivity observed, this can be offset by increasing the density of traps in the area.

Accounting for spatially heterogeneous conditions in local-scale surveillance strategies: case study of the biosecurity insect pest, grape phylloxera (Daktulosphaira vitifoliae (Fitch))

BACKGROUND

Surveillance strategies are often standardized and completed on grid patterns to detect pest incursions quickly; however, it may be possible to improve surveillance through more targeted observation that accounts for landscape heterogeneity, dispersal and the habitat requirements of the invading organism. We simulated pest spread at a local scale, using grape phylloxera (Daktulosphaira vitifoliae (Fitch)) as a case study, and assessed the influence of incorporating spatial heterogeneity into surveillance compared with current, standard surveillance strategies.

RESULTS

Time to detection and spread within and beyond the vineyard were reduced by conducting surveys that target sampling effort in soil that is highly suitable for the invading pest in comparison with standard surveillance strategies. However, these outcomes were dependent on the virulence level of phylloxera because phylloxera is a complex pest with multiple genotypes that influence spread and detectability.

CONCLUSION

Targeting surveillance strategies based on local-scale spatial heterogeneity can decrease the time to detection without increasing the survey cost, and surveillance that targets highly suitable soil is the most efficient strategy for detecting new incursions. In addition, combining targeted surveillance strategies with buffer zones and hygiene procedures, and updating surveillance strategies as additional species information becomes available, will further decrease the risk of pest spread. © 2018 Society of Chemical Industry.

Do an invasive organism's dispersal characteristics affect how we should search for it?

We investigated how an invading organism's dispersal characteristics affect the efficacy of different surveillance strategies aimed at detecting that organism as it spreads following a new incursion. Specifically, we assessed whether, out of the surveillance strategies tested, the best surveillance strategy for an organism varied depending on the way it disperses. We simulated the spread of invasive organisms with different dispersal characteristics including leptokurtic and non-leptokurtic kernels with different median dispersal distances and degrees of kurtosis. We evaluated surveillance strategies with different sampling arrangements, densities and frequencies. Surveillance outcomes compared included the time to detection, the total spread of the invasion and the likelihood of the invasion reaching new areas. Overall, dispersal characteristics affected the surveillance outcomes, but the grid surveillance arrangement consistently performed best in terms of early detection and reduced spread within and between fields. Additionally, the results suggest that dispersal characteristics may influence spread to new areas and surveillance strategies. Therefore, knowledge on an invasive organism's dispersal characteristics may influence how we search for it and how we manage the invasion to prevent spread to new areas.

Species Identification in Malaise Trap Samples by DNA Barcoding Based on NGS Technologies and a Scoring Matrix

The German Barcoding initiatives BFB and GBOL have generated a reference library of more than 16,000 metazoan species, which is now ready for applications concerning next generation molecular biodiversity assessments. To streamline the barcoding process, we have developed a meta-barcoding pipeline: We pre-sorted a single malaise trap sample (obtained during one week in August 2014, southern Germany) into 12 arthropod orders and extracted DNA from pooled individuals of each order separately, in order to facilitate DNA extraction and avoid time consuming single specimen selection. Aliquots of each ordinal-level DNA extract were combined to roughly simulate a DNA extract from a non-sorted malaise sample. Each DNA extract was amplified using four primer sets targeting the CO1-5’ fragment. The resulting PCR products (150-400bp) were sequenced separately on an Illumina Mi-SEQ platform, resulting in 1.5 million sequences and 5,500 clusters (coverage ≥10; CD-HIT-EST, 98%). Using a total of 120,000 DNA barcodes of identified, Central European Hymenoptera, Coleoptera, Diptera, and Lepidoptera downloaded from BOLD we established a reference sequence database for a local CUSTOM BLAST. This allowed us to identify 529 Barcode Index Numbers (BINs) from our sequence clusters derived from pooled Malaise trap samples. We introduce a scoring matrix based on the sequence match percentages of each amplicon in order to gain plausibility for each detected BIN, leading to 390 high score BINs in the sorted samples; whereas 268 of these high score BINs (69%) could be identified in the combined sample. The results indicate that a time consuming presorting process will yield approximately 30% more high score BINs compared to the non-sorted sample in our case. These promising results indicate that a fast, efficient and reliable analysis of next generation data from malaise trap samples can be achieved using this pipeline.

Eradication of Invading Insect Populations: From Concepts to Applications

Eradication is the deliberate elimination of a species from an area. Given that international quarantine measures can never be 100% effective, surveillance for newly arrived populations of nonnative species coupled with their eradication represents an important strategy for excluding potentially damaging insect species. Historically, eradication efforts have not always been successful and have sometimes been met with public opposition. But new developments in our understanding of the dynamics of low-density populations, the availability of highly effective treatment tactics, and bioeconomic analyses of eradication strategies offer new opportunities for developing more effective surveillance and eradication programs. A key component that connects these new developments is the harnessing of Allee effects, which naturally promote localized species extinction. Here we review these developments and suggest how research might enhance eradication strategies.