Community Science Program Research Articles

Public Reporting and Perception of Invasive Pheretimoid “Jumping Worms” in the Northeastern United States

Pheretimoid earthworms (“Jumping Worms”) are Asian annelids with characteristics that make them effective invaders in the northeastern United States. Because many species of Jumping Worms thrive in wood mulches, gardening practices may play a significant role in distributing them. Despite mounting evidence that Jumping Worms can cause damage to gardens and natural ecosystems, the current range of Jumping Worms in North America is poorly known. We compiled reports of Jumping Worms from many different data sources to better understand the potential for amateur community scientists to contribute information regarding undescribed populations of these invasive species. Additionally, we conducted a survey of Cooperative Extension Master Gardener volunteers to better understand the perception of these species within the gardening community and attempts at control. Amateur reporting from community-science programs and gardeners resulted in a large number of potential, undescribed Jumping Worm populations, especially in areas unstudied by the small number of earthworm researchers in our study region. Within the gardening community, the perception of Jumping Worms is less favorable compared to other earthworms, largely owing to their perceived negative ecological effects in gardens and natural ecosystems. As a result, homeowners frequently attempt to control their abundance. Gardeners and community scientists can importantly contribute to our understanding of the range and negative effects of invasive Jumping Worms in the Northeast.

Distribution models using semi-structured community science data outperform unstructured-data models for a data-poor species, the Plain Tyrannulet

Abstract Modeling the distribution of a data-poor species is challenging due to a reliance on unstructured data that often lacks relevant information on sampling and produces coarse-resolution outputs of varying accuracy. Data on sampling effort associated with higher-quality, semi-structured data derived from some community science programs can be used to produce more precise models of distribution, albeit at a cost of using fewer data. Here, we used semi-structured data to model the seasonal ranges of the Plain Tyrannulet (Inezia inornata), a poorly known Austral–Neotropical migrant, and compared predictive performance to models built with the full unstructured dataset of the species. By comparing these models, we examined the relatively unexplored tradeoff between data quality and data quantity for modeling of a data-sparse species. We found that models using semi-structured data outperformed unstructured-data models in the predictive accuracy metrics (mean squared error, area under the curve, kappa, sensitivity, and specificity), despite using only 30% of the available detection records. Moreover, semi-structured models were more biologically accurate, indicating that the tyrannulet favors arboreal habitats in dry and hot lowlands during the breeding season (Chaco region) and is associated with proximity to rivers in tropical and wet areas during the nonbreeding season (Pantanal, Beni, and southwest Amazonia). We demonstrate that more detailed insights into distributional patterns can be gained from even small quantities of data when the data are analyzed appropriately. The use of semi-structured data promises to be of wide applicability even for data-poor bird species, helping refine information on distribution and habitat use, needed for effective assessments of conservation status.

The Rapid Rise of Next-Generation Natural History

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

Domestic Cat Abundance and Activity Across a Residential Land Use Gradient

Free-ranging domestic cats are a detriment to wildlife and humans by preying on native species and transmitting disease. As a result, removing free-ranging cats from the landscape has become a conservation and public health priority. Estimating cat population size with an unbiased sampling design, however, especially in human-dominated areas, is logistically challenging and rarely done. The lack of robust cat population sampling limits our understanding of where cats pose risks, which is important for evaluating management strategies, such as trap-remove or trap-neuter-return. We hypothesized that cat abundance and activity both depend on human land use and demographics. Using a network of sites participating in a community science program, we conducted transect and camera trap surveys to test predictions of cat population abundance and activity across a gradient of residential land use intensity. Both sampling methods determined that cat abundance was greatest in areas with intermediate human population density and lower educational attainment. Transect data also provided evidence that cat abundance was greatest at intermediate levels of impervious surface cover (e.g., road and buildings), while data from camera traps also showed that cat abundance was positively associated with household income. Using counts of cats observed on cameras, we found that the timing of cat activity varied depending on the degree of urban intensity. Cats were more strictly nocturnal in medium and high intensity residential land-use areas, possibly because a greater proportion of these cats are unowned or because they avoid human activity. These results suggest that transect surveys conducted during the day may undercount cats in urban environments where unowned free-ranging cats predominate. Taken together, our results highlight the importance of incorporating human demographics, land use patterns, and urban context in estimating the abundance of free-ranging cats to better inform management decisions and improve conservation outcomes.

Climate change impacts on natural icons: Do phenological shifts threaten the relationship between peak wildflowers and visitor satisfaction?

Climate change will affect the timing of natural features of recreational interest, like fall colors, salmon migration, and wildflower blooms; and may therefore alter social-ecological relationships. For example, if fewer recreational visits are aligned with seasonal events of interest, visitor satisfaction could be affected. To explore this possibility at Mount Rainier National Park, we combined data from a community science program (MeadoWatch – MW) with hiking trip reports posted to a hiking organization (Washington Trails Association – WTA). We first explored how peak flowering, WTA trip reports, and visitation varied across years that differed in snow disappearance, a climatic factor that correlates with flowering phenology. We found that wildflower blooms tracked snow disappearance more closely than did trip reports and park visitation, implying a decreasing proportion of future visitors will experience peak wildflower blooms. We next extracted sentiment related to specific trail-experiences (e.g., wildflowers, views) and overall hike satisfaction from WTA trip reports. While wildflowers were a positive component in overall hiker satisfaction, other non-seasonal trail experiences also had positive effects. In all, a shifting wildflower season that is less accessible to visitors could alter perceptions of natural areas like Mount Rainier National Park. Countering negative social-ecological impacts could be achieved by highlighting non-seasonal aspects of the visitor experience, or alternatively, communicating the altered timing of the peak wildflower season while also increasing accessibility during this time. Such actions likely require partnerships between managers of natural areas, interpretive staff, and scientists that study seasonal phenomena of recreational interest.

Wildfire smoke affects detection of birds in Washington State

AbstractWildfire smoke is likely to have direct health effects on birds as well as influence movement, vocalization, and other avian behaviors. These behavioral changes may affect if and how birds are observed in the wild, although research on the effects of wildfire smoke on bird behavior is limited. To evaluate how wildfire smoke affects detection of birds, we combined data from eBird, an online community science program, with data from an extensive network of air quality monitors in the state of Washington over a 4-year period. We assessed how PM2.5, a marker of smoke pollution, affected the probability of observing 71 bird species during the wildfire seasons of 2015–2018 using bird observations from 62,908 eBird checklists. After accounting for habitat, weather conditions, seasonality, and survey effort, we found that PM2.5 affected the probability of observing 37% of study species. The ambient concentration of PM2.5 was negatively associated with the probability of observing 16 species and positively associated with the probability of observing 10 species, indicating that birds exhibit species-specific behavioral changes during wildfire smoke events that influence how they are observed. Our results suggest that wildfire smoke impacts the presence, availability, and/or perceptibility of birds. Impacts of smoke pollution on human observers, such as impaired visibility, may also influence detection of birds. These results provide a foundation for developing mechanistic hypotheses to explain how birds, and our studies of them, are impacted by wildfire smoke. Given the projected increase in large-scale wildfire smoke events under future climate change scenarios, understanding how birds are affected by wildfire smoke—and how air pollution may influence our ability to detect them—are important next steps to inform wildlife research and avian conservation.

Community Science for Coastal Acidification Monitoring and Research

Ocean and coastal acidification (OCA) present a unique set of sustainability challenges at the human-ecological interface. Extensive biogeochemical monitoring that can assess local acidification conditions, distinguish multiple drivers of changing carbonate chemistry, and ultimately inform local and regional response strategies is necessary for successful adaptation to OCA. However, the sampling frequency and cost-prohibitive scientific equipment needed to monitor OCA are barriers to implementing the widespread monitoring of dynamic coastal conditions. Here, we demonstrate through a case study that existing community-based water monitoring initiatives can help address these challenges and contribute to OCA science. We document how iterative, sequential outreach, workshop-based training, and coordinated monitoring activities through the Northeast Coastal Acidification Network (a) assessed the capacity of northeastern United States community science programs and (b) engaged community science programs productively with OCA monitoring efforts. Our results (along with the companion manuscript) indicate that community science programs are capable of collecting robust scientific information pertinent to OCA and are positioned to monitor in locations that would critically expand the coverage of current OCA research. Furthermore, engaging community stakeholders in OCA science and outreach enabled a platform for dialogue about OCA among other interrelated environmental concerns and fostered a series of co-benefits relating to public participation in resource and risk management. Activities in support of community science monitoring have an impact not only by increasing local understanding of OCA but also by promoting public education and community participation in potential adaptation measures.

COVID-19 impacts on participation in large scale biodiversity-themed community science projects in the United States

Shutdowns associated with the COVID-19 pandemic have had extensive impacts on professional and volunteer-based biodiversity and conservation efforts. We evaluated the impact of the widespread pandemic-related closures in the spring of 2020 on participation patterns and rates on a national and a state-by-state basis in the United States in four biodiversity-themed community science programs: eBird, eButterfly, iNaturalist, and Nature's Notebook. We compared the number of participants, observations submitted, and proportion of observations collected in urban environments in spring 2020 to the expected values for these metrics based on activity in the previous five years (2015–2019), which in many cases exhibited underlying growth.At the national scale, eButterfly and Nature's Notebook exhibited declines in the number of participants and number of observations submitted during the spring of 2020 and iNaturalist and eBird showed growth in both measures. On a state-by-state basis, the patterns varied geographically and by program. The more popular programs – iNaturalist and eBird – exhibited increases in the Eastern U.S. in both the number of observations and participants and slight declines in the West. Further, there was a widespread increase in observations originating from urban areas, particularly in iNaturalist and eBird. Understanding the impacts of lockdowns on participation patterns in these programs is crucial for proper interpretation of the data. The data generated by these programs are highly valuable for documenting impacts of pandemic-related closures on wildlife and plants and may suggest patterns seen in other community science programs and in other countries.

Synoptic assessment of coastal total alkalinity through community science

Comprehensive sampling of the carbonate system in estuaries and coastal waters can be difficult and expensive because of the complex and heterogeneous nature of near-shore environments. We show that sample collection by community science programs is a viable strategy for expanding estuarine carbonate system monitoring and prioritizing regions for more targeted assessment. ‘Shell Day’ was a single-day regional water monitoring event coordinating coastal carbonate chemistry observations by 59 community science programs and seven research institutions in the northeastern United States, in which 410 total alkalinity (TA) samples from 86 stations were collected. Field replicates collected at both low and high tides had a mean standard deviation between replicates of 3.6 ± 0.3 µmol kg−1 (σ mean ± SE, n = 145) or 0.20 ± 0.02%. This level of precision demonstrates that with adequate protocols for sample collection, handling, storage, and analysis, community science programs are able to collect TA samples leading to high-quality analyses and data. Despite correlations between salinity, temperature, and TA observed at multiple spatial scales, empirical predictions of TA had relatively high root mean square error >48 µmol kg−1. Additionally, ten stations displayed tidal variability in TA that was not likely driven by low TA freshwater inputs. As such, TA cannot be predicted accurately from salinity using a single relationship across the northeastern US region, though predictions may be viable at more localized scales where consistent freshwater and seawater endmembers can be defined. There was a high degree of geographic heterogeneity in both mean and tidal variability in TA, and this single-day snapshot sampling identified three patterns driving variation in TA, with certain locations exhibiting increased risk of acidification. The success of Shell Day implies that similar community science based events could be conducted in other regions to not only expand understanding of the coastal carbonate system, but also provide a way to inventory monitoring assets, build partnerships with stakeholders, and expand education and outreach to a broader constituency.

Tradeoffs of using place‐based community science for urban biodiversity monitoring

AbstractCommunity science, the enlisting of volunteers to collect biodiversity data, is now common and widespread. In theory, the benefits of this model are complementary: community science programs produce useful datasets while engaging the public in conservation. However, in practice there may be tradeoffs regarding data quality, economic cost, and public engagement, which are rarely quantified. To assess program structure and relative outputs, we evaluated the tradeoffs associated with (a) employing paid technicians or (b) recruiting community science volunteers to collect bird and butterfly data for an urban biodiversity project. We found mixed results for data quality; the probability of detecting human‐adapted species was similar between technicians and community scientists, but community scientists were less likely to detect human‐sensitive species and overreported the abundance of human‐adapted birds. Habitat use estimates for four out of five species were comparable between the two datasets, although uncertainty was greater for community science data. Community scientists were more efficient in terms of economic cost, producing one and a half times more bird and two times more butterfly surveys and detections per paid work‐hour. Community scientists improved their ability to identify local species (birds by 16%; butterflies by 31%). Lastly, community scientists reported an increased interest in educational or volunteer programs after participating in monitoring but were less likely to report an increased interest in taking conservation action. To improve data quality, we recommend that training focus on identifying human‐sensitive species and tracking multiple individuals of the same species during surveys. To catalyze changes in attitudes, programs should focus on recruiting members of the public with diverse preexisting attitudes toward conservation. Although we demonstrate some shortcomings, our findings add to a growing body of literature that suggests community science can increase scientific literacy and efficiently produce data of similar quality to technicians, particularly for common species.

Having it all: hybridizing conventional and community science monitoring for enhanced data quality and cost savings

Large-scale monitoring is used to track population trends for many ecologically and economically important wildlife species. Often, population monitoring involves professional staff travelling to collect data (i.e., conventional monitoring) or in efforts to reduce monitoring costs, by engaging volunteers (i.e., community science). Although many studies have discussed the advantages and disadvantages of conventional vs. community science monitoring, few have made direct, quantitative comparisons between these two approaches. We compared data quality and financial costs between contemporaneous and overlapping conventional and community science programs for monitoring a major forest pest, the spruce budworm ( Choristoneura fumiferanae Clem.). Although community science trapping sites were clumped around urban areas, abundance estimates from the programs were strongly spatially correlated. However, annual program expenditures were nearly four times lower in the community science versus the conventional program. We modelled a hypothetical hybrid model of the two programs, which provided full spatial coverage and potentially the same data, but at half the cost of the conventional program and with the added opportunity for public engagement. Our study provides a unique quantitative analysis of merits and costs of conventional versus community science monitoring. Our study offers insights on how to assess wildlife monitoring programs where multiple approaches exist.

Place and transformative learning in climate change focused community science

Community science involves the co-creation of scientific pursuits, learning, and outcomes and is presented as a transformative practice for community engagement and environmental governance. Emphasizing critical reflection, this study adopts Mezirow’s conception of transformative learning to theorize the transformative capacity of community science. Findings from interviews with participants in a community science program reveal critical reflection, although instances acknowledging attitudes and beliefs without challenging personal assumptions were more common. Program elements most likely to prompt participants to identify beliefs, values, and assumptions include data collection and interaction in team dynamics, whereas data collection in a novel environment was most likely to prompt participants to challenge their beliefs, values, and assumptions. A review of 71 climate change focused programs further demonstrates the extent that program designs support transformative learning. Key features of the community science landscape like the broad inclusion of stated learning objectives offer a constructive starting point for deepening transformative capacity, while the dominance of contributory program designs stands as a likely roadblock. Overall, this study contributes by applying a developed field to theorize transformation in relation to community science and by highlighting where facilitators should focus program design efforts to better promote transformation toward environmental sustainability.

I have a kit and I create worlds: synthetic ecology from synthetic genomes

The genome is the blueprint for life. A genome sequence can be transcribed and translated by molecular machines to assemble an organism capable of replication, sensation, and response. Organisms respond to each other, forming intricate interaction webs that manifest as ecosystems, defining the world we live in and rely on. It all starts with a genome. And if we can build a genome, we can create worlds. This article is protected by copyright. All rights reserved.

CORRIGENDUM

Restoration EcologyVolume 28, Issue 5 p. 1308-1308 CORRIGENDUMFree Access CORRIGENDUM This article corrects the following: Repeated mowing to restore remnant native grasslands invaded by nonnative annual grasses: upsides and downsides above and below ground Justin M. Valliere, Susan Balch, Carole Bell, Carlos Contreras, Bridget E. Hilbig, Volume 27Issue 2Restoration Ecology pages: 261-268 First Published online: August 30, 2018 First published: 29 September 2020 https://doi.org/10.1111/rec.13280AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL In Valliere et al. (2019), the terms ‘citizen scientists/science’ mentioned in the following sections were incorrect and should be changed to ‘community scientists/science’. On page 262, the third subsection title under ‘Methods’ section should read as ‘Community Science Program’. On page 267, the last sentence in the subsection ‘Other Benefits of Mowing’ should read as ‘… with researchers and community scientists can provide practitioners …’. On page 267, the second sentence in the ‘Acknowledgment’ section should read as ‘… the success of this community science project.” The authors apologize for this previously non-inclusive language. LITURATURE CITED Valliere JM, Balch S, Bell C, Contreras C, Hilbig BE (2019) Repeated mowing to restore remnant native grasslands invaded by nonnative annual grasses: upsides and downsides above and below ground. Restoration Ecology 27: 261– 268 Volume28, Issue5September 2020Pages 1308-1308 Restoration Ecology - Message to authors, reviewers, editorial board During this time of mass disruption, be advised that we appreciate there will be a slower pace for all. Restoration Ecology understands that reviews and decisions may be delayed; responses from authors may be delayed. There are no consequences for delays. We ask all to be patient. The EIC and Managing Editor work remotely as is (in different countries) so we already work from ‘home’. We are attempting to add this message to our communications (not as easy because the Editors don’t have total editing rights) and reduce the normal reminder emails to reflect this uncertain time. If you receive our normal email correspondence reminding you of deadlines, we are waiving these and asking only that you let us know, if possible, of delays exceeding a month. Stephen Murphy, EIC ReferencesRelatedInformation

Plant science decadal vision 2020-2030: Reimagining the potential of plants for a healthy and sustainable future.

Plants, and the biological systems around them, are key to the future health of the planet and its inhabitants. The Plant Science Decadal Vision 2020–2030 frames our ability to perform vital and far‐reaching research in plant systems sciences, essential to how we value participants and apply emerging technologies. We outline a comprehensive vision for addressing some of our most pressing global problems through discovery, practical applications, and education. The Decadal Vision was developed by the participants at the Plant Summit 2019, a community event organized by the Plant Science Research Network. The Decadal Vision describes a holistic vision for the next decade of plant science that blends recommendations for research, people, and technology. Going beyond discoveries and applications, we, the plant science community, must implement bold, innovative changes to research cultures and training paradigms in this era of automation, virtualization, and the looming shadow of climate change. Our vision and hopes for the next decade are encapsulated in the phrase reimagining the potential of plants for a healthy and sustainable future. The Decadal Vision recognizes the vital intersection of human and scientific elements and demands an integrated implementation of strategies for research (Goals 1–4), people (Goals 5 and 6), and technology (Goals 7 and 8). This report is intended to help inspire and guide the research community, scientific societies, federal funding agencies, private philanthropies, corporations, educators, entrepreneurs, and early career researchers over the next 10 years. The research encompass experimental and computational approaches to understanding and predicting ecosystem behavior; novel production systems for food, feed, and fiber with greater crop diversity, efficiency, productivity, and resilience that improve ecosystem health; approaches to realize the potential for advances in nutrition, discovery and engineering of plant‐based medicines, and "green infrastructure." Launching the Transparent Plant will use experimental and computational approaches to break down the phytobiome into a "parts store" that supports tinkering and supports query, prediction, and rapid‐response problem solving. Equity, diversity, and inclusion are indispensable cornerstones of realizing our vision. We make recommendations around funding and systems that support customized professional development. Plant systems are frequently taken for granted therefore we make recommendations to improve plant awareness and community science programs to increase understanding of scientific research. We prioritize emerging technologies, focusing on non‐invasive imaging, sensors, and plug‐and‐play portable lab technologies, coupled with enabling computational advances. Plant systems science will benefit from data management and future advances in automation, machine learning, natural language processing, and artificial intelligence‐assisted data integration, pattern identification, and decision making. Implementation of this vision will transform plant systems science and ripple outwards through society and across the globe. Beyond deepening our biological understanding, we envision entirely new applications. We further anticipate a wave of diversification of plant systems practitioners while stimulating community engagement, underpinning increasing entrepreneurship. This surge of engagement and knowledge will help satisfy and stoke people's natural curiosity about the future, and their desire to prepare for it, as they seek fuller information about food, health, climate and ecological systems.

Monitoring the world's bird populations with community science data

Systematic monitoring of species across their geographic ranges is a critical part of conservation but it is resource-intensive, costly, and difficult to organize and maintain in the long-term. Large-scale community science programs like eBird may improve our ability to monitor bird populations, particularly in tropical regions where formal studies are lacking. Here, we estimated population trends for nearly 9000 bird species using global eBird birdwatching data and compared our trends to the population trends designated by BirdLife International. We calculated the rate of agreement between eBird and BirdLife trends and examined the effects of latitudinal affiliation, threat status, number of eBird checklists, eBird trend, BirdLife trend and BirdLife trend derivation on the rate of agreement. We also used a randomization approach to compare observed rates of agreement with the rates of agreement expected by chance alone. We show that the rate of agreement was marginally better than expected by chance and improved significantly for temperate region species of Least Concern with more checklists, and species that eBird or BirdLife identified as increasing. Our results suggest that eBird data are not currently adequate for monitoring populations of the majority of the world's bird species, especially in the developing world where systematic surveys are essential. Increased local participation in community science initiatives like eBird may improve our ability to effectively monitor species. Furthermore, it is important to assess the accuracy of BirdLife trends and the manner in which they are derived, especially for species where BirdLife and eBird data trends disagree.

Using Bumble Bee Watch to investigate the accuracy and perception of bumble bee (Bombus spp.) identification by community scientists.

Community science programs provide an opportunity to gather scientific data to inform conservation policy and management. This study examines the accuracy of community science identifications submitted to the North American Bumble Bee Watch program on a per species level and as compared to each species’ conservation status, as well as users (members of the public) and experts (those with expertise in the field of bumble bee biology) perceived ease of species identification. Photos of bumble bees (Hymenoptera: Apidae: Bombus) are submitted to the program by users and verified (species name corrected or assigned as necessary) by an expert. Over 22,000 records from over 4,900 users were used in the analyses. Accuracy was measured in two ways: percent agreement (percent of all records submitted correctly by users) and veracity (percent of all verified records submitted correctly by the users). Users generally perceived it harder to identify species than experts. User perceptions were not significantly different from the observed percent agreement or veracity, while expert perceptions were significantly different (overly optimistic) from the observed percent agreement but not the veracity. We compared user submitted names to final expert verified names and found that, for all species combined, the average percent agreement was 53.20% while the average veracity was 55.86%. There was a wide range in percent agreement values per species, although sample size and the role of chance did affect some species agreements. As the conservation status of species increased to higher levels of extinction risk, species were increasingly more likely to have a lower percent agreement but higher levels of veracity than species of least concern. For each species name submitted, the number of different species verified by experts varied from 1 to 32. Future research may investigate which factors relate to success in user identification through community science. These findings could play a role in informing the design of community science programs in the future, including for use in long-term and national-level monitoring of wild pollinators.

Community science participants gain environmental awareness and contribute high quality data but improvements are needed: insights from Bumble Bee Watch

Bumble Bee Watch is a community science program where participants submit photos of bumble bees from across Canada and the United States for expert verification. The data can be used to help better understand bumble bee biology and aid in their conservation. Yet for community science programs like this to be successful and sustainable, it is important to understand the participant demographics, what motivates them, and the outcomes of their participation, as well as areas that are working well or could be improved. It is also important to understand who verifies the submissions, who uses the data and their views on the program. Of the surveyed users, most participate to contribute to scientific data collection (88%), because of a worry about bees and a desire to help save them (80%), to learn more about species in their property (63%) or region (56%), and because of a personal interest (59%). About 77% report increased awareness of species diversity, while 84% report improvement in their identification skills. We found that 81% had at least one college or university degree. There were more respondents from suburban and rural areas than urban areas, but area did not affect numbers of submissions. While half were between 45 and 64 years of age, age did not influence motivation or number of submissions. Respondents were happy with the program, particularly the website resources, the contribution to knowledge and conservation efforts, the educational values, and the ability to get identifications. Areas for improvement included app and website functionality, faster and more detailed feedback, localized resources, and more communication. Most respondents participate rarely and have submitted fewer than ten records, although about five percent are super users who participate often and submit more than fifty records. Suggested improvements to the program may increase this participation rate. Indeed, increased recruitment and retention of users in general is important, and advertising should promote the outcomes of participation. Fifteen experts responded to a separate survey and were favorable of the program although there were suggestions on how to improve the verification process and the quality of the submitted data. Suggested research questions that could be asked or answered from the data included filling knowledge gaps (species diversity, ranges, habitat, phenology, floral associations, etc.), supporting species status assessments, effecting policy and legislation, encouraging habitat restoration and management efforts, and guiding further research. However, only about half have used data from the project to date. Further promotion of Bumble Bee Watch and community science programs in general should occur amongst academia, conservationists, policy makers, and the general public. This would help to increase the number and scope of submissions, knowledge of these species, interest in conserving them, and the overall program impact.

Community science validates climate suitability projections from ecological niche modeling.

Climate change poses an intensifying threat to many bird species and projections of future climate suitability provide insight into how species may shift their distributions in response. Climate suitability is characterized using ecological niche models (ENMs), which correlate species occurrence data with current environmental covariates and project future distributions using the modeled relationships together with climate predictions. Despite their widespread adoption, ENMs rely on several assumptions that are rarely validated in situ and can be highly sensitive to modeling decisions, precluding their reliability in conservation decision-making. Using data from a novel, large-scale community science program, we developed dynamic occupancy models to validate near-term climate suitability projections for bluebirds and nuthatches in summer and winter. We estimated occupancy, colonization, and extinction dynamics across species' ranges in the United States in relation to projected climate suitability in the 2020s, and used a Gibbs variable selection approach to quantify evidence of species-climate relationships. We also included a Bird Conservation Region strata-level random effect to examine among-strata variation in occupancy that may be attributable to land-use and ecoregional differences. Across species and seasons, we found strong evidence that initial occupancy and colonization were positively related to 2020 climate suitability, illustrating an independent validation of projections from ENMs across a large geographic area. Random strata effects revealed that occupancy probabilities were generally higher than average in core areas and lower than average in peripheral areas of species' ranges, and served as a first step in identifying spatial patterns of occupancy from these community science data. Our findings lend much-needed support to the use of ENM projections for addressing questions about potential climate-induced changes in species' occupancy dynamics. More broadly, our work highlights the value of community scientist observations for ground-truthing projections from statistical models and for refining our understanding of the processes shaping species' distributions under a changing climate.

Tracking insect outbreaks: a case study of community-assisted moth monitoring using sex pheromone traps

Insect outbreaks can cover vast geographic areas making it onerous to cost-effectively monitor populations to address management or ecological questions. Community science (or citizen science), which entails engaging the public to assist with data collection, provides a possible solution to this challenge for the spruce budworm ( Choristoneura fumiferana Clemens), a major defoliating pest in North America. Here, we lay out the Budworm Tracker Program, a contributory community science program developed to help monitor spruce budworm moths throughout eastern Canada. The program outsources free pheromone trap kits to volunteers who periodically check and collect moths from their traps throughout the budworm flight period, then return them in a prepaid envelope to the organizers. Over three years, the program engaged an average of 216–375 volunteers and yielded a data return rate of 68%–89%, for a total of 16 311–54 525 moths per year. Volunteer retention among years was 71%–89%. Data from this program offer compelling evidence for the range of long-distance moth dispersal. Although our program was designed for spruce budworm, this template could easily be adapted for forestry, urban forestry, and agricultural systems to monitor any of the numerous organisms for which there is an established trapping method.