Citizen Science and Monitoring Forest Pests: a Beneficial Alliance?

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.

The ongoing range expansion of the invasive oak lace bug across Europe: current occurrence and potential distribution under climate change

In recent years, the oak lace bug, Corythucha arcuata, has emerged as a significant threat to European oak forests. This species, native to North America, has in the last two decades rapidly extended its range in Europe, raising concerns about its potential impact on the continent's invaluable oak populations. To address this growing concern, we conducted an extensive study to assess the distribution, colonization patterns, and potential ecological niche of the oak lace bug in Europe. We gathered 1792 unique presence coordinates from 21 Eurasian countries, utilizing diverse sources such as research observations, citizen science initiatives, GBIF database, and social media reports. To delineate the realized niche and future distribution, we employed an ensemble species distribution modelling (SDM) framework. Two future greenhouse gas scenarios (RCP 4.5 and RCP 8.5) were considered across three-time intervals (2021-2040, 2061-2080, and 2081-2100) to project and evaluate the species' potential distribution in the future. Our analysis revealed that significant hotspots rich in host species occurrence for this invasive insect remain uninvaded so far, even within its suitable habitat. Furthermore, the native ranges of Turkey oak (Quercus cerris L.) and Hungarian oak (Quercus frainetto L.) species offer entirely suitable environments for the oak lace bug. In contrast, the pedunculate oak and sessile oak distribution ranges currently show only 40 % and 50 % suitability for colonization, respectively. However, our predictive models indicate a significant transformation in the habitat suitability of the oak lace bug, with suitability for these two oak species increasing by up to 90 %. This shift underlines an evolving landscape where the oak lace bug may exploit more of its available habitats than initially expected. It emphasises the pressing need for proactive measures to manage and stop its expanding presence, which may lead to a harmful impact on the oak population across the European landscape.

Image segmentation for pest detection of crop leaves by improvement of regional convolutional neural network

Pest detection is important for crop cultivation. Crop leaf is the main place of pest invasion. Current technologies to detect crop pests have constraints, such as low efficiency, storage demands and limited precision. Image segmentation is a fast and efficient computer-aided detection technology. High resolution image capture solidly supports the crucial processes in discerning pests from images. Study of analytical methods help parse information in the images. In this paper, a regional convolutional neural network (R-CNN) architecture is designed in combination with the radial bisymmetric divergence (RBD) method for enhancing the efficiency of image segmentation. As a special application of RBD, the hierarchical mask (HM) is produced to endorse detection and classification of the leaf-dwelling pests, offering enhanced efficiency and reduced storage requirements. Moreover, to deal with some mislabeled data, a threshold variable is introduced to adjust a fault-tolerant mechanism into HM, to generate a novel threshold-based hierarchical mask (TbHM). Consequently, the hierarchical mask R-CNN (HM-R-CNN) model and the threshold-based hierarchical mask R-CNN (TbHM-R-CNN) model are established to detect various types of healthy and pest-invasive crop leaves to select the regional image features that are rich in pest information. Then simple linear iterative clustering (SLIC) method is incorporation to finish the image segmentation for the classification of pest invasion. The models are tuned and optimized, then validated. The most optimized modeling results are from the TbHM-R-CNN model, with the classification accuracy of 96.2%, the recall of 97.5% and the F1 score of 0.982. Additionally, the HM-R-CNN model observed appreciable results second only to the best model. These results indicate that the proposed methodologies are well-suited for training and testing a dataset of plant diseases, offering heightened accuracy in pest classification. This study revealed that the proposed methods significantly outperform the existing techniques, marking a substantial improvement over current methods.

Monitoring urban biological invasions using citizen science: the polyphagous shot hole borer (Euwallacea fornicatus)

Benefits provided by urban trees are increasingly threatened by non-native pests and pathogens. Monitoring of these invasions is critical for the effective management and conservation of urban tree populations. However, a shortage of professionally collected species occurrence data is a major impediment to assessments of biological invasions in urban areas. We applied data from iNaturalist to develop a protocol for monitoring urban biological invasions using the polyphagous shot hole borer (PSHB) invasion in two urban areas of South Africa. iNaturalist records for all known PSHB reproductive host species were used together with data on localities of sites for processing plant biomass to map priority monitoring areas for detecting new and expanding PSHB infestations. Priority monitoring areas were also identified using the distribution of Acer negundo, a highly susceptible host that serves as a sentinel species for the detection of PSHB infestations. iNaturalist data provided close to 9000 observations for hosts in which PSHB is known to reproduce in our study area (349 of which were A. negundo). High-priority areas for PSHB monitoring include those with the highest density of PSHB reproductive hosts found close to the 140 plant biomass sites identified. We also identified high-priority roads for visual and baited trap surveys, providing operational guidance for practitioners. The monitoring protocol developed in this study highlights the value of citizen or community science data in informing the management of urban biological invasions. It also advocates for the use of platforms such as iNaturalist as essential tools for conservation monitoring in urban landscapes.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10340-024-01744-7.

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.

A Decade of Hidden Phytoplasmas Unveiled Through Citizen Science

Climate change is impacting agriculture in many ways, and a contribution from all is required to reduce the imminent losses related to it. Recently, it has been shown that citizen science could be a way to trace the impact of climate change. However, how can citizen science be applied in plant pathology? Here, using as an example a decade of phytoplasma-related diseases reported by growers, agronomists, and citizens in general, and confirmed by a government laboratory, we explored how to better value plant pathogen monitoring data. Through this collaboration, we found that in the last decade, 34 hosts have been affected by phytoplasmas; 9, 13, and 5 of these plants were, for the first time, reported phytoplasma hosts in eastern Canada, all of Canada, and worldwide, respectively. Another finding of great impact is the first report of a 'Candidatus Phytoplasma phoenicium'-related strain in Canada, while 'Ca. P. pruni' and 'Ca. P. pyri' were reported for the first time in eastern Canada. These findings will have a great impact on the management of phytoplasmas and their insect vectors. Using these insect-vectored bacterial pathogens, we show the need for new strategies that can allow fast and accurate communication between concerned citizens and those institutions confirming their observations.[Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Invasion Genetics of the Horse-Chestnut Leaf Miner, Cameraria ohridella (Lepidoptera: Gracillariidae), in European Russia: A Case of Successful Involvement of Citizen Science in Studying an Alien Insect Pest

Based on the intensive monitoring conducted by our team and volunteers in 2021, the secondary range of an alien horse-chestnut leaf miner, Cameraria ohridella Deschka & Dimić, 1986 (Lepidoptera: Gracillariidae), was specified in European Russia. This invasive pest was confirmed in 24 out of 58 administrative regions of Russia, which it has occupied for approximately 16 years. Analysis of the COI mtDNA gene sequenced in 201 specimens collected in 21 regions of the European part of Russia indicates the occurrence of two haplotypes (A and B), which are also present in the secondary range of C. ohridella in Eastern and Western Europe. The haplotype A dominated and was present in 87.5% of specimens from European Russia. In 2021, C. ohridella produced spectacular outbreaks in Aesculus hippocastanum in southern Russia, where it damaged more than 50% of the leaves in trees in 24 out of 30 distant localities. In the south of the country, the pest infested Acer pseudoplatanus, whereas other species of Acer of European, East Asian, and North American origin showed no signs of attacks. Taking into account that Ae. hippocastanum is present in most regions of European Russia, we expect a further range expansion of C. ohridella up to the Ural Mountains.