Citizen science contributes to our knowledge of invasive plant species distributions

Catching invasives with curiosity: the importance of passive biosecurity surveillance systems for invasive forest pest detection

First detections of nonnative insect species are often made by curious members of the public rather than by specialists or trained professionals. Passive surveillance is a crucial component of national biosecurity surveillance, highlighted by early detection case studies of several prominent nonnative arthropod pests (e.g., Asian longhorned beetle [ALB], Jorō spider, spotted lanternfly). These examples demonstrate that curiosity and the recognition of novelty in the natural world, along with enabling technology and systems, are a critical part of early detection and effective invasive species management. This is particularly impactful when dealing with conspicuous pests or for new and emerging nonnative species that have yet to be detected in a new location. Data from historical and recent accounts of first detections of ALB incursions and other invasive forest pests underscore the need to invest in passive surveillance reporting systems and fully integrate public observations into existing surveillance frameworks. New automated approaches streamline the assessment of public observations and can generate pest alerts to initiate a formal regulatory assessment. Biodiversity monitoring platforms, such as iNaturalist, provide a focal point for community engagement and aggregate verified public observations. Empowering proactive reporting of biological novelty provides needed support for early detection of invasive species. Embracing the public as active members of the surveillance community can be cost effective and lead to the greatest gains in the proactive management of invasive species around the world.

A within-lake occupancy model for starry stonewort, Nitellopsis obtusa, to support early detection and monitoring

To efficiently detect aquatic invasive species early in an invasion when control may still be possible, predictions about which locations are likeliest to be occupied are needed at fine scales but are rarely available. Occupancy modeling could provide such predictions given data of sufficient quality and quantity. We assembled a data set for the macroalga starry stonewort (Nitellopsis obtusa) across Minnesota and Wisconsin, USA, where it is a new and high-priority invader. We used these data to construct a multi-season, single-species spatial occupancy model that included biotic, abiotic, and movement-related predictors. Distance to the nearest access was an important occurrence predictor, highlighting the likely role boats play in spreading starry stonewort. Fetch and water depth also predicted occupancy. We estimated an average detection probability of 63% at sites with mean non-N. obtusa plant cover, declining to ~ 38% at sites with abundant plant cover, especially that of other Characeae. We recommend that surveyors preferentially search for starry stonewort in areas of shallow depth and high fetch close to boat accesses. We also recommend searching during late summer/early fall when detection is likelier. This study illustrates the utility of fine-scale occupancy modeling for predicting the locations of nascent populations of difficult-to-detect species.

Hidden cargo: The impact of historical shipping trade on the recent-past and contemporary non-native flora of northeastern United States

PREMISE

Understanding establishment and spread of non-native plants is important in the face of a homogenizing global flora. While many studies focus on successful, invasive species, fewer have studied failed plant introductions. Until the early 1900s, large quantities of ship ballast, often containing foreign plant propagules, were deposited in New Jersey (USA). The resulting ballast flora is documented in extensive herbarium records, providing us a unique opportunity to analyze successes and failures of novel plant species introductions.

METHODS

We used digitized specimens from 75 herbaria to study 264 non-native species introduced into New Jersey through 19th century ballast deposition. We used spatial (density-based clustering; HDBSCAN) and temporal analyses of species retention and geographic spread to quantify disappearance rate, survival, and dispersion through time and define trajectory groups.

RESULTS

Four distinct trajectory groups were identified: waif (only present during import; 32% of species), short-term (disappeared quickly; 20%), established-limited spread (survives locally, 30%), and established-widespread (widespread, 18%). Species disappearance rate was highest during ballast deposition and decreased soon after deposition stopped around 1900. Spatial patterns showed a strong association with 19th century railroads for inland dispersal from ports. The disappearance rate and spatial analyses are robust to herbarium collection bias.

CONCLUSIONS

This study using New Jersey as a model is one of the few documenting multispecies successes and failures in inadvertent plant introductions. Results reveal distinct trends in species establishment and geographic spread and highlight the utility of herbarium specimens in answering questions that span large time scales.

Citizen Science Improves the Known and Potential Distribution of a Strong Wetland Invader: Implications for Niche Modeling and Invasion Management

Invasive alien species are one of the main causes of biodiversity loss and ecosystem alteration. Obtaining up-to-date occurrence records and accurate invasion risk maps has become crucial to develop timely and effective management strategies. Unfortunately, gathering and validating distribution data can be labor-intensive and time-consuming, with different data sources unavoidably leading to biases in the results. In this study, we evaluated the performance of a tailored citizen science project compared with other data sources, in mapping the current and potential distribution of Iris pseudacorus, a strong invasive alien plant in Argentina. To do so, we used geographic information systems and ecological niche modeling with Maxent, and compared data from: i) a citizen science tailored project; ii) the Global Biodiversity Information Facility (GBIF); and iii) an exhaustive professional data collection (i.e. field samplings across Argentina, literature and collections review). Results suggest that the citizen science tailored project provided a larger and more diversified amount of data compared to the other sources. All data-sources showed good performance in the ecological niche models, however, data from the tailored citizen science project predicted a greater suitable area, including regions not yet reported. This allowed us to better identify critical and vulnerable areas, where management and prevention strategies are necessary. Professional data provided more reports in non-urban areas, whereas citizen science based data sources (i.e. GBIF and the citizen science project conducted in this study) reported more sites in urban areas, which indicates that different data-sources are complementary and there is a big potential in combining methods. We encourage the use of tailored citizen science campaigns to gather a more diverse amount of data, generating better knowledge about aquatic invasive species and helping decision-making in ecosystem management.

Drivers of systematic bias in alien plant species distribution data

Among the main challenges in modelling biological invasion is a lack of valid data on the absence of invasive species. Absence data are important for assessing the reliability of models, but multiple surveys at a location are needed. In practice, omission errors are more frequent than commission errors. We therefore quantified how eliminating potentially biased areas from invasive species distribution models (iSDMs) affected the models' performance, and we assessed how the distribution of biased areas correlated with environmental factors. We hypothesized that for neophytes, the distribution of biased areas corresponds to specific land relief and/or particular landscape and land use, but not the density of roads and urbanized areas. The data on neophytes were obtained from a distribution atlas covering approximately 31,000 km² in Central Europe overlaid with a 2 × 2 km square grid. One hundred fifty-three species were used for modelling neophyte richness, and negative residuals from the model were assumed to indicate biased squares. Twenty invasive species were used as an independent dataset for testing the effect of excluding the biased squares on iSDM performance. The exclusion of biased squares increased the iSDM performance from an area under the curve value of 0.73 to 0.78. The best results were obtained by excluding 30 % of the squares from the original dataset. The presence of damp sites explained the distribution of biased squares; the density of roads and urbanized areas had no impact. The applied method allows distinguishing biased, plausibly undersampled squares in a species distribution atlas, the exclusion of which significantly improves iSDM performance. The results suggest that the commonly observed low sampling effort in areas distant from communication routes and urbanized areas was not crucial in modelling invasive species distribution, which can be related to smaller neophyte richness in remote areas resulting from low propagule pressure.

Identifying, reducing, and communicating uncertainty in community science: a focus on alien species

Community science (also often referred to as citizen science) provides a unique opportunity to address questions beyond the scope of other research methods whilst simultaneously engaging communities in the scientific process. This leads to broad educational benefits, empowers people, and can increase public awareness of societally relevant issues such as the biodiversity crisis. As such, community science has become a favourable framework for researching alien species where data on the presence, absence, abundance, phenology, and impact of species is important in informing management decisions. However, uncertainties arising at different stages can limit the interpretation of data and lead to projects failing to achieve their intended outcomes. Focusing on alien species centered community science projects, we identified key research questions and the relevant uncertainties that arise during the process of developing the study design, for example, when collecting the data and during the statistical analyses. Additionally, we assessed uncertainties from a linguistic perspective, and how the communication stages among project coordinators, participants and other stakeholders can alter the way in which information may be interpreted. We discuss existing methods for reducing uncertainty and suggest further solutions to improve data reliability. Further, we make suggestions to reduce the uncertainties that emerge at each project step and provide guidance and recommendations that can be readily applied in practice. Reducing uncertainties is essential and necessary to strengthen the scientific and community outcomes of community science, which is of particular importance to ensure the success of projects aimed at detecting novel alien species and monitoring their dynamics across space and time.

The Citizen Science Paradox

Citizen science (CS) is now very popular in ecology. The number of scientific publications referencing CS has increased steadily over the past 15 years, with more than 1150 publications today. However, the multiplicity of research involved suggests that this number is highly underestimated. Based on this paradox, a literature review on CS shows that while its formalization in 2009 facilitated its referencing, about 70% of the publications are not referenced using CS as keyword. To understand this under-representation, an analysis of 149 publications related to the famous Christmas Bird Count program shows that this underestimation is not mainly related to the diversity of keywords used to describe CS, but rather to the fact that CS is mainly considered as a method (four publications out of five). The results also show that taking into account the whole text of a publication would represent a substantial improvement for the analysis of scientific databases, whatever the field of research.

Overwinter survival of Corbicula fluminea in a central Minnesota lake

Although Corbicula fluminea has been one of the more prolific freshwater invasive species in the world, previous studies have suggested a low probability for overwinter survival in northern latitudes without an artificially created thermal refuge. The discovery of live C. fluminea in a central Minnesota lake absent any known thermal refuge in 2020 presented an opportunity to further evaluate the overwinter survival and population structure of C. fluminea at the presumed edge of their potential range. The population was monitored from December 2020 through September 2021 alongside water temperature to better understand at which temperatures C. fluminea survived and if the population structure suggested reproduction occurring in the lake. We documented live C. fluminea in temperatures as low as 0.3°C. Shell size of recovered individuals suggested multiple cohorts, and the appearance of a new cohort at the end of the study, indicating active reproduction in the lake and suggesting the population had likely been present in the lake for at least two winters by the conclusion of the study period. Our findings provide evidence of the survival below historically documented lower lethal temperature limits and suggests adaptations to modeling predicting suitable habitat, both present and in a changing climate, are necessary to better assess risk of invasion by this species.

A review of volunteers’ motivations to monitor and control invasive alien species

People make an important contribution to the study and management of biological invasions, as many monitoring and control projects rely heavily on volunteer assistance. Understanding the reasons why people participate in such projects is critical for successful recruitment and retention of volunteers. We used a meta-synthesis approach to extract, analyze and synthesize the available information from 28 selected studies investigating motivations of volunteers to engage in monitoring and control of invasive alien species (IAS). Our findings show how motivations fit three broad themes, reflecting environmental concerns, social motivations, and personal reasons. An important outcome of this study is the description of motivations that are unique to the IAS context: supporting IAS management, protecting native species and habitats, and livelihood/food/income protection or opportunities. In addition, our study reflects on important methodological choices for investigating volunteer motivations as well as ethical issues that may arise in practice. We conclude with a set of recommendations for project design and future research on volunteer motivations in IAS contexts, emphasizing the importance of collaboration with social scientists.

Automatic detection of alien plant species in action camera images using the chopped picture method and the potential of citizen science

Monitoring and detection of invasive alien plant species are necessary for effective management and control measures. Although efforts have been made to detect alien trees using satellite images, the detection of alien herbaceous species has been difficult. In this study, we examined the possibility of detecting non-native plants using deep learning on images captured by two action cameras. We created a model for each camera using the chopped picture method. The models were able to detect the alien plant Solidago altissima (tall goldenrod) and obtained an average accuracy of 89%. This study proved that it is possible to automatically detect exotic plants using inexpensive action cameras through deep learning. This advancement suggests that, in the future, citizen science may be useful for conducting distribution surveys of alien plants in a wide area at a low cost.

Citizen science reveals current distribution, predicted habitat suitability and resource requirements of the introduced African Carder Bee Pseudoanthidium (Immanthidium) repetitum in Australia

The introduction of non-native bee species is a major driver of ecosystem change resulting in the spread of non-native weeds, alterations to plant-pollinator interactions and competition with native species for food and nesting resources. Our lack of ecological information for many non-native organisms hinders our ability to understand the impacts of species introductions. This is often compounded by the Wallacean Shortfall—a lack of adequate knowledge of a species’ distribution in geographic space. In Australia, the African carder bee (Pseudoanthidium (Immanthidium) repetitum) was first observed in 2000 and has since become one of the most common bees in some regions. Despite its rapid population increase and range expansion, little is known about the ecology or distribution of P. repetitum. In this study, we determine the flower preferences, current distribution and predicted areas at risk of future invasion of P. repetitum using opportunistic data collected from citizen science websites, social media and museum records. We found that the current distribution of P. repetitum in Australia encompasses approximately 332,000 km2 concentrated along the eastern coast. We found considerable suitable habitat outside the current distribution including biodiversity hotspots and world heritage listed natural areas. Pseudoanthidium repetitum foraged on a wide range of plants from many families and can thus be classified as a generalist forager (polylectic). Our results suggest that P. repetitum is well suited for continued expansion in coastal Australia. Our results demonstrate the effective application of opportunistic data in overcoming knowledge gaps in species ecology and modelling of introduced species distribution.

OUP accepted manuscript

The invasive plant Alliaria petiolata (garlic mustard) has spread throughout forest understory and edge communities in much of North America, but its persistence, density, and impacts have varied across sites and time. Surveying the literature since 2008, we evaluated both previously proposed and new mechanisms for garlic mustard's invasion success and note how they interact and vary across ecological contexts. We analyzed how and where garlic mustard has been studied and found a lack of multisite and longitudinal studies, as well as regions that may be under- or overstudied, leading to poor representation for understanding and predicting future invasion dynamics. Inconsistencies in how sampling units are scaled and defined can also hamper our understanding of invasive species. We present new conceptual models for garlic mustard invasion from a macrosystems perspective, emphasizing the importance of synergies and feedbacks among mechanisms across spatial and temporal scales to produce variable ecological contexts.

Evaluating the Fitness for Use of Citizen Science Data for Wildlife Monitoring

Contributory citizen science programs focused on ecological monitoring can produce fine-grained and expansive data sets across spatial and temporal scales. With this data collection potential, citizen scientists can significantly impact the ability to monitor ecological patterns. However, scientists still harbor skepticism about using citizen science data in their work, generally due to doubts about data quality. Numerous peer-reviewed articles have addressed data quality in citizen science. Yet, many of these methods are not useable by third-party scientists (scientists who are not directly involved in the citizen science program). In addition, these methods generally capture internal data quality rather than a dataset’s potential to be used for a specific purpose. Assessing data fitness for use represents a promising approach to evaluating data accuracy and quality for different applications and contexts. In this article, we employ a Spatial, Temporal, Aptness, and Application (STAAq) assessment approach to assess data fitness for use of citizen science datasets. We tested the STAAq assessment approach through a case study examining the distribution of caribou in Denali National Park and Preserve. Three different datasets were used in the test, Map of Life data (a global scale citizen science mobile application for recording species observations), Ride Observe and Record data (a program sponsored by the park staff where incentivized volunteers observe species in the park), and conventionally collected radio collar data. The STAAq assessment showed that the Map of Life and Ride Observe and Record program data are fit for monitoring caribou distribution in the park. This data fitness for use approach is a promising way to assess the external quality of a dataset and its fitness to address particular research or monitoring questions. This type of assessment may help citizen science skeptics see the value and potential of citizen science collected data and encourage the use of citizen science data by more scientists.

Citizen science and niche modeling to track and forecast the expansion of the brown marmorated stinkbug Halyomorpha halys (Stål, 1855)

Halyomorpha halys (Stål, 1855), the Brown Marmorated StinkBug (BMSB) is a highly successful invasive species native to eastern Asia that managed to spread into North America and Europe in recent decades. We set up a citizen science survey to monitor BMSB expansion in France in 2012 and analyzed the data it yielded between 2012 and 2019 to examine the local expansion of the insect. These data were gathered with occurrences form various sources (GBIF, literature) to calibrate a species niche model and assess potential current BMSB range. We evaluated the potential changes to the BMSB range due to climate change by projecting the model according to 6 global circulation models (GCM) and the shared socio-economic pathways SSP245 in two time periods 2021-2040 and 2041-2060. Citizen science allowed to track BMSB expansion in France and provided information about its phenology and its habitat preferences. The model highlighted the potential for further range expansion in Europe and illustrated the impact of climate change. These results could help managing the current BMSB invasion and the framework of this survey could contribute to a better preparedness of phytosanitary authorities either for the BMSB or other invasive pests.

Monitoring Extreme Impacts of Rugulopteryx okamurae (Dictyotales, Ochrophyta) in El Estrecho Natural Park (Biosphere Reserve). Showing Radical Changes in the Underwater Seascape

The invasive macroalga Rugulopteryx okamurae represents an unprecedented case of bioinvasion by marine macroalgae facing the European coasts. Since the first apparition of the species in the Strait of Gibraltar in 2015, its fast dispersion along the introduced habitats constitutes a real challenge to develop monitoring strategies that ahead of its impacts. The present study uses three different approaches to address impacts on the benthic ecosystems, at the same time offers relevant data for future management actions in El Estrecho Natural Park (PNE). Information obtained by monitoring permanent sentinel stations revealed a significant loss in resident species coverage after the moment of maximum growth in 2017. Thus, despite coverage of R. okamurae did not strongly varied in the latter years, impacts generated remain high in the habitats studied. Estimations of the invasive species coverage by combining cartographic image analysis and in situ data predicted a major occupation (over 85% coverage) between 10 and 30 m, coinciding with the maximum rocky surface areas (m2) mapped on the PNE. Furthermore, a Citizen Science research collaboration evidenced impacts on the benthic seascape through an ad hoc exploration of images that allowed a “before” and “after” comparison of the invasion process in the same geographic locations. This has made it possible to graphically demonstrate severe changes in the underwater seascape and, therefore, the general impact of this new biological invasion. The spatial colonization estimations combined with the impacts reported by both scientific [Sessile Bioindicators in Permanent Quadrats (SBPQ) sentinel stations] and civilian (Citizen Science) monitoring methodologies claim the urgent development of further studies that allow the design of monitoring strategies against R. okamurae expansion across the Mediterranean and Atlantic waters.

Trends and gaps in the use of citizen science derived data as input for species distribution models: A quantitative review

Citizen science (CS) currently refers to the participation of non-scientist volunteers in any discipline of conventional scientific research. Over the last two decades, nature-based CS has flourished due to innovative technology, novel devices, and widespread digital platforms used to collect and classify species occurrence data. For scientists, CS offers a low-cost approach of collecting species occurrence information at large spatial scales that otherwise would be prohibitively expensive. We examined the trends and gaps linked to the use of CS as a source of data for species distribution models (SDMs), in order to propose guidelines and highlight solutions. We conducted a quantitative literature review of 207 peer-reviewed articles to measure how the representation of different taxa, regions, and data types have changed in SDM publications since the 2010s. Our review shows that the number of papers using CS for SDMs has increased at approximately double the rate of the overall number of SDM papers. However, disparities in taxonomic and geographic coverage remain in studies using CS. Western Europe and North America were the regions with the most coverage (73%). Papers on birds (49%) and mammals (19.3%) outnumbered other taxa. Among invertebrates, flying insects including Lepidoptera, Odonata and Hymenoptera received the most attention. Discrepancies between research interest and availability of data were as especially important for amphibians, reptiles and fishes. Compared to studies on animal taxa, papers on plants using CS data remain rare. Although the aims and scope of papers are diverse, species conservation remained the central theme of SDM using CS data. We present examples of the use of CS and highlight recommendations to motivate further research, such as combining multiple data sources and promoting local and traditional knowledge. We hope our findings will strengthen citizen-researchers partnerships to better inform SDMs, especially for less-studied taxa and regions. Researchers stand to benefit from the large quantity of data available from CS sources to improve global predictions of species distributions.

Ready, Set, Go: Community Science Field Campaign Reveals Habitat Preferences of Nonnative Asian Earthworms in an Urban Landscape

Asian pheretimoid earthworms of the genera Amynthas and Metaphire (jumping worms) are leading a new wave of coinvasion into Northeastern and Midwestern states, with potential consequences for native organisms and ecosystem processes. However, little is known about their distribution, abundance, and habitat preferences in urban landscapes—areas that will likely influence their range expansion via human-driven spread. We led a participatory field campaign to assess jumping worm distribution and abundance in Madison, Wisconsin, in the United States. By compressing 250 person-hours of sampling effort into a single day, we quantified the presence and abundance of three jumping worm species across different land-cover types (forest, grassland, open space, and residential lawns and gardens), finding that urban green spaces differed in invasibility. We show that community science can be powerful for researching invasive species while engaging the public in conservation. This approach was particularly effective in the present study, where broad spatial sampling was required within a short temporal window.

People's Knowledge and Risk Perceptions of Invasive Plants in Metro Vancouver, British Columbia, Canada

Effective management of invasive plants conserves biodiversity values, reduces economic costs, and minimizes negative impacts on human health. Fostering people's awareness of invasive plants is one of the most cost-effective approaches in preventing the spread and introduction of invasive plants. Therefore, this study aims to understand (1) people's knowledge and risk perceptions, (2) associations between risk perceptions and demographics, and (3) people's willingness to support current management strategies in the Metro Vancouver region, British Columbia, Canada. An online survey was carried out and received 356 responses across the region. We found that people's knowledge and risk perceptions of invasive plants were ecologically oriented. Older respondents perceived higher risks of invasive plants. Among respondents of the same age, annual income higher than $50,000 was associated with higher levels of risk perception. Respondents who had professional and/or recreational group memberships perceived higher economic risks. Respondents highly supported activities that they could take part in directly, such as community invasive pulls and native species planting. Overall, our findings aid managers in allocating appropriate funding or tailoring outreach efforts to different aspects of invasive plants as well as groups/communities where people's knowledge and risk perceptions of invasive plants are low.

Observer-oriented approach improves species distribution models from citizen science data

Citizen science platforms are increasingly growing, and, storing a huge amount of data on species locations, they provide researchers with essential information to develop sound strategies for species conservation. However, the lack of information on surveyed sites (i.e., where the observers did not record the target species) and sampling effort (e.g., the number of surveys at a given site, by how many observers, and for how much time) strongly limit the use of citizen science data. Thus, we examined the advantage of using an observer-oriented approach (i.e., considering occurrences of species other than the target species collected by the observers of the target species as pseudo-absences and additional predictors relative to the total number of observations, observers, and days in which locations were collected in a given sampling unit, as proxies of sampling effort) to develop species distribution models. Specifically, we considered 15 mammal species occurring in Italy and compared the predictive accuracy of the ensemble predictions of nine species distribution models carried out considering random pseudo-absences versus observer-oriented approach. Through cross-validations, we found that the observer-oriented approach improved species distribution models, providing a higher predictive accuracy than random pseudo-absences. Our results showed that species distribution modeling developed using pseudo-absences derived citizen science data outperform those carried out using random pseudo-absences and thus improve the capacity of species distribution models to accurately predict the geographic range of species when deriving robust surrogate of sampling effort.

Outlier detection methods to improve the quality of citizen science data

Citizen science involves public participation in research, usually through volunteer observation and reporting. Data collected by citizen scientists are a valuable resource in many fields of research that require long-term observations at large geographic scales. However, such data may be perceived as less accurate than those collected by trained professionals. Here, we analyze the quality of data from a plant phenology network, which tracks biological response to climate change. We apply five algorithms designed to detect outlier observations or inconsistent observers. These methods rely on different quantitative approaches, including residuals of linear models, correlations among observers, deviations from multivariate clusters, and percentile-based outlier removal. We evaluated these methods by comparing the resulting cleaned datasets in terms of time series means, spatial data coverage, and spatial autocorrelations after outlier removal. Spatial autocorrelations were used to determine the efficacy of outlier removal, as they are expected to increase if outliers and inconsistent observations are successfully removed. All data cleaning methods resulted in better Moran's I autocorrelation statistics, with percentile-based outlier removal and the clustering method showing the greatest improvement. Methods based on residual analysis of linear models had the strongest impact on the final bloom time mean estimates, but were among the weakest based on autocorrelation analysis. Removing entire sets of observations from potentially unreliable observers proved least effective. In conclusion, percentile-based outlier removal emerges as a simple and effective method to improve reliability of citizen science phenology observations.

The role of passive surveillance and citizen science in plant health

The early detection of plant pests and diseases is vital to the success of any eradication or control programme, but the resources for surveillance are often limited. Plant health authorities can however make use of observations from individuals and stakeholder groups who are monitoring for signs of ill health. Volunteered data is most often discussed in relation to citizen science groups, however these groups are only part of a wider network of professional agents, land-users and owners who can all contribute to significantly increase surveillance efforts through "passive surveillance". These ad-hoc reports represent chance observations by individuals who may not necessarily be looking for signs of pests and diseases when they are discovered. Passive surveillance contributes vital observations in support of national and international surveillance programs, detecting potentially unknown issues in the wider landscape, beyond points of entry and the plant trade. This review sets out to describe various forms of passive surveillance, identify analytical methods that can be applied to these "messy" unstructured data, and indicate how new programs can be established and maintained. Case studies discuss two tree health projects from Great Britain (TreeAlert and Observatree) to illustrate the challenges and successes of existing passive surveillance programmes. When analysing passive surveillance reports it is important to understand the observers' probability to detect and report each plant health issue, which will vary depending on how distinctive the symptoms are and the experience of the observer. It is also vital to assess how representative the reports are and whether they occur more frequently in certain locations. Methods are increasingly available to predict species distributions from large datasets, but more work is needed to understand how these apply to rare events such as new introductions. One solution for general surveillance is to develop and maintain a network of tree health volunteers, but this requires a large investment in training, feedback and engagement to maintain motivation. There are already many working examples of passive surveillance programmes and the suite of options to interpret the resulting datasets is growing rapidly.

Double-edged effects of climate change on plant invasions: Ecological niche modeling global distributions of two invasive alien plants

The prediction of the potential distribution of invasive alien species is key for the control of their proliferation. This study developed ensemble niche models to explore the distribution patterns of Cecropia peltata and Ulex europaeus under baseline and future conditions, as well as the factors that regulate them. The models were based on occurrence records as well as climate, land-use and topography datasets. Climatic factors played a stronger role than land-use and topographical factors in their distribution patterns. Additionally, temperature seasonality and temperature annual range were the optimal predictor for the global distributions of C. peltata and U. europaeus, respectively. Under the baseline-RCP 8.5 scenario in 2070, significant increases in habitat suitability for C. peltata were generally detected in tropical regions, while for U. europaeus under the same condition, significant increases in habitat suitability were generally observed in west coast of South America and Europe, suggesting the impacts of climate changes on species distribution may be species specific. The contrast changes of suitable habitat areas for U. europaeus under the baseline-2.6 and 8.5 scenarios may suggest that the scenarios of climate changes may modify its distribution patterns and variations in suitable habitats. The double-edged effects of global warming on plant invasions may be a result of the scenario specific climate change and the species-specific responses to changes in climate. Our findings highlight the importance of climate change scenario specific and species-specific research on the impact of climate change on plant invasions.

Citizen science provides added value in the monitoring for coastal non-indigenous species

Continuous and comprehensive monitoring is one of the most important practices to trace changes in the state of the environment and target management efforts. Yet, governmental resources are often insufficient for monitoring all required environmental parameters, and therefore authorities have started to utilize citizen observations to supplement and increase the scale of monitoring. The aims of the present study were to show the potential of citizen science in environmental monitoring by utilising citizen observations of the non-indigenous Harris mud crab Rhithropanopeus harrisii in Finnish waters, where coastal monitoring is insufficient to estimate the distribution and spread of non-indigenous species. Harris mud crab has shown measurable impact locally and is considered invasive. For reporting the status of invasions to national and European authorities and planning for potential eradication efforts, up to date knowledge on NIS ranges are needed. Citizen observations on the species were collected from the first observation onwards between 2009 and 2018, at first via email and later through an active citizen observation web portal (Invasive Alien Species Portal). The outcomes of the study indicate that species-specific citizen observations can be a beneficial addition to supplement national monitoring programs to fulfil legislative reporting requirements and to target potential management. Recognizable species and geographical areas with low biodiversity provide a good opportunity to utilize citizen observations. Moreover, citizen observations may enable distribution assessments for certain species that would otherwise require excessive resources and sampling efforts.

Assessing the current and potential future distribution of four invasive forest plants in Minnesota, U.S.A., using mixed sources of data

Invasive plants are an ongoing subject of interest in North American forests, owing to their impacts on forest structure and regeneration, biodiversity, and ecosystem services. An important component of studying and managing forest invaders involves knowing where the species are, or could be, geographically located. Temporal and environmental context, in conjunction with spatially-explicit species occurrence information, can be used to address this need. Here, we predict the potential current and future distributions of four forest plant invaders in Minnesota: common buckthorn (Rhamnus cathartica), glossy buckthorn (Frangula alnus), garlic mustard (Alliaria petiolata), and multiflora rose (Rosa multiflora). We assessed the impact of two different climate change scenarios (IPCC RCP 6.0 and 8.5) at two future timepoints (2050s and 2070s) as well as the importance of occurrence data sources on the potential distribution of each species. Our results suggest that climate change scenarios considered here could result in a potential loss of suitable habitat in Minnesota for both buckthorn species and a potential gain for R. multiflora and A. petiolata. Differences in predictions as a result of input occurrence data source were most pronounced in future climate projections.

Potential distribution of two invasive pineapple pests under climate change

BACKGROUND

The number of global invasive species has significantly increased during the past two centuries due to globalization. The understanding of species invasion under climate change is crucial for sustainable biodiversity conservation, community dynamics, ecosystem function, and resource distribution. Two invasive species, Dysmicoccus brevipes (Cockerell) and D. neobrevipes (Beardsley) have greatly expanded their ranges during recent years. These insects are now considered as extremely serious pests for various plants, especially pineapple. In addition, they are the primary vectors for pineapple wilt associated virus. However, the potential distribution range and management strategies for these pests are unclear.

RESULTS

In this study, potential risk maps were developed for these pests with MaxEnt (maximum entropy) based on occurrence data under different environmental variables. The potential distributions of these pests were projected for 2050s and 2070s under three climate change scenarios as described in the Special Report on Emissions Scenarios of the Intergovernmental Panel on Climate Change. Results showed that both pests have similar potential distributions, with high environmental suitability in South America, Africa and South Asia. In addition, potential range expansions or reductions were predicted under different climate change scenarios. The annual mean temperature was the most important factor, accounting for 43.4% of D. brevipes distribution. The minimum temperature of coldest month and mean temperature of coldest quarter was found to be responsible for 90.3% of D. neobrevipes distribution.

CONCLUSION

This research provided a theoretical reference framework to develop policies in the management and control of these invasive pests. © 2019 Society of Chemical Industry.

Biological invasion: Long term monitoring of the macroalgal flora of a major European harbor complex

The marine macroflora of the ports of Le Havre and Antifer have been studied by citizen scientists since the late 1970s. In addition to analysis of the previous results, the field study was extended from 2010 to 2018. A total of 97 and 62 macroalgae were identified, respectively, including 14 NIS (non-indigenous species), the latter number being certainly an underestimate since microscopic species were not exhaustively sought and given the high number of cryptogenic species encountered. No new primary introduction of NIS for the NE Atlantic has been detected since the late 1970s. The origin of NIS and vector(s) of introduction were investigated. For all NIS, the donor region is the Indo-Pacific. Two likely vectors have been identified: maritime traffic for earlier introductions, and shellfish imports for more recent ones. The role of these ports and maritime traffic in the processes of introduction is discussed.

Opportunistic citizen science data transform understanding of species distributions, phenology, and diversity gradients for global change research

Opportunistic citizen science (CS) programs allow volunteers to report species observations from anywhere, at any time, and can assemble large volumes of historic and current data at faster rates than more coordinated programs with standardized data collection. This can quickly provide large amounts of species distributional data, but whether this focus on participation comes at a cost in data quality is not clear. Although automated and expert vetting can increase data reliability, there is no guarantee that opportunistic data will do anything more than confirm information from professional surveys. Here, we use eButterfly, an opportunistic CS program, and a comparable dataset of professionally collected observations, to measure the amount of new distributional species information that opportunistic CS generates. We also test how well opportunistic CS can estimate regional species richness for a large group of taxa (>300 butterfly species) across a broad area. We find that eButterfly contributes new distributional information for >80% of species, and that opportunistically submitting observations allowed volunteers to spot species ~35 days earlier than professionals. Although eButterfly did a relatively poor job at predicting regional species richness by itself (detecting only about 35-57% of species per region), it significantly contributed to regional species richness when used with the professional dataset (adding ~3 species that had gone undetected in professional surveys per region). Overall, we find that the opportunistic CS model can provide substantial complementary species information when used alongside professional survey data. Our results suggest that data from opportunistic CS programs in conjunction with professional datasets can strongly increase the capacity of researchers to estimate species richness, and provide unique information on species distributions and phenologies that are relevant to the detection of the biological consequences of global change.

Managing invasive species

Invasive species pose considerable harm to native ecosystems and biodiversity and frustrate and at times fascinate the invasive species management and scientific communities. Of the numerous non-native species established around the world, only a minority of them are invasive and noxious, whereas the majority are either benign or in fact beneficial. Agriculture in North America, for example, would look dramatically different if only native plants were grown as food crops and without the services of the European honey bee as a pollinator. Yet the minority of species that are invasive negatively alter ecosystems and reduce the services they provide, costing governments, industries, and private citizens billions of dollars annually. In this review, I briefly review the consequences of invasive species and the importance of remaining vigilant in the battle against them. I then focus on their management in an increasingly connected global community.

Citizen Science as a Tool in Biological Recording—A Case Study of Ailanthus altissima (Mill.) Swingle

Non-native invasive species frequently appear in urban and non-urban ecosystems and may become a threat to biodiversity. Some of these newcomers are introduced accidentally, and others are introduced through a sequence of events caused by conscious human decisions. Involving the general public in biodiversity preservation activities could prevent the negative consequences of these actions. Accurate and reliable data collecting is the first step in invasive species management, and citizen science can be a useful tool to collect data and engage the public in science. We present a case study of biological recording of tree of heaven (Ailanthus altissima (Mill.) Swingle) using a participatory citizen model. The first goal in this case study was to develop a cheap, widely accessible, and effective inventory method, and to test it by mapping tree of heaven in Croatia. A total of 90.61 km of roads and trails was mapped; 20 single plants and 19 multi-plant clusters (mapped as polygons) were detected. The total infested area was 2610 m2. The second goal was to educate citizens and raise awareness of this invasive species. The developed tool and suggested approach aided in improving invasive risk management in accordance with citizen science principles and can be applied to other species or areas.

Quality of non-expert citizen science data collected for habitat type conservation status assessment in Natura 2000 protected areas

EU biodiversity conservation policy is based on the Habitats Directive (92/43/EC), which aims that habitat types and species of Community interest should reach ‘favourable conservation status’. To this end, Member States are obliged to perform periodic assessment of species and habitat conservation status through biodiversity monitoring, which, in almost all cases, was performed by experts implementing standardized field protocols. Here, we examine the quality of data collected in the field by non-experts (citizen scientists) for the conservation status assessment of habitat types, and specifically for the criteria ‘typical species’, ‘specific structures and functions’, and ‘pressures and threats’. This task is complicated and demands different types of field data. We visited two Natura 2000 sites and investigated four habitat types (two in each site) with non-experts and compared their data to the data collected by experts for accuracy, completeness and spatial arrangement. The majority of the non-expert data were accurate (i.e. non-experts recorded information they observed in the field), but they were incomplete (i.e. non-experts detected less information than the experts). Also, non-experts chose their sampling locations closer to the edge of the habitat, i.e. in more marginal conditions and thus in potentially more degraded conditions, than experts.