Science Monitoring Programs Research Articles

FreshWater Watch: Investigating the Health of Freshwater Ecosystems, from the Bottom Up

Freshwater ecosystems are increasingly facing major global and local stressors, while monitoring surface water status by regulatory agencies is often limited by financial and political constraints. Citizen science–based approaches with robust quality control and training can support regulatory monitoring and decision-making. Herein, we outline the criteria used to develop a citizen science monitoring program for water quality, based on a standardized methodology designed to support the Agenda 2030 indicator 6.3.2 and the EU’s Water Framework Directive. We explore the evolution of protocols used to ensure data robustness and transferability and examine the utility of contextual information registered by citizen scientists. We present laboratory and field experiments conducted to validate chemical and optical methods. Using the data from more than 80 projects across 4 biogeographical regions, we explore consistencies and differences in seasonal and spatial trends in macronutrient concentrations between regions. Our results indicate that nitrate and phosphate concentrations tend to increase in areas with agricultural intensification and industrial land use. Seasonally, nitrate concentrations reach a maximum in spring and autumn in temperate regions, while phosphate levels are highest in summer and autumn, reaching a minimum in winter. We also found that observations of algal blooms coincided with periods of lower nitrate concentrations. Importantly, data of ecological, chemical, and optical conditions recorded by citizen scientists are being used by local and regional stakeholders in managing freshwater ecosystems. This study reveals the potential for scaling citizen science–based monitoring programs to contribute towards a global assessment of water quality.

Testing of Shoreline Erosion Monitoring Methodologies for Heritage at Risk Sites: Pockoy Island, South Carolina, USA

Abstract We review shoreline monitoring methodologies used by members of the South Carolina Department of Natural Resources (SCDNR) Archaeology, Geology, and Wildlife Biology teams from February 2021 to December 2022 on Pockoy Island in Charleston County, South Carolina, USA. Our project objectives were to better understand the driving forces behind the landward movement of the shoreline (transgression), to apply new understanding to the rate of shoreline erosion of the island that directly impacts the Pockoy Island Shell Ring Complex (38CH2533), and to establish best practice for future community science monitoring efforts. Each member of our team used a different shoreline monitoring methodology (a nested methodology approach). Multiple unoccupied aerial vehicle (UAV)-derived orthoimagery datasets, on-the-ground transect measurements, and Arrow Gold real-time kinematic (RTK) unit measurements have been collected monthly following significant storms or king (perigean) tide events. Moving forward, the erosion transect approach tested within this project will serve as the foundation for community science monitoring at heritage at-risk sites in South Carolina. In this article, we introduce initial efforts in establishing a community science monitoring program in South Carolina that will influence future research, land management, and policy, and we propose how our research might be adapted for other sites at risk.

Genomic characterization of Volzhskoe tick virus (Bunyaviricetes) from a Hyalomma marginatum tick, Hungary

Hyalomma marginatum, a vector for the high-consequence pathogen, the Crimean–Congo hemorrhagic fever virus (CCHFV), needs particular attention due to its impact on public health. Although it is a known vector for CCHFV, its general virome is largely unexplored. Here, we report findings from a citizen science monitoring program aimed to understand the prevalence and diversity of tick-borne pathogens, particularly focusing on Hyalomma ticks in Hungary. In 2021, we identified one adult specimen of Hyalomma marginatum and subjected it to Illumina-based viral metagenomic sequencing. Our analysis revealed sequences of the uncharacterized Volzhskoe tick virus, an unclassified member of the class Bunyaviricetes. The in silico analysis uncovered key genetic regions, including the glycoprotein and the RNA-dependent RNA polymerase (RdRp) coding regions. Phylogenetic analysis indicated a close relationship between our Volzhskoe tick virus sequences and other unclassified Bunyaviricetes species. These related species of unclassified Bunyaviricetes were detected in vastly different geolocations. These findings highlight the remarkable diversity of tick specific viruses and emphasize the need for further research to understand the transmissibility, seroreactivity or the potential pathogenicity of Volzhskoe tick virus and related species.

Bee monitoring by community scientists: comparing a collections-based program with iNaturalist.

Bee monitoring, or widespread efforts to document bee community biodiversity, can involve data collection using lethal (specimen collections) or non-lethal methods (observations, photographs). Additionally, data can be collected by professional scientists or by volunteer participants from the general public. Collection-based methods presumably produce more reliable data with fewer biases against certain taxa, while photography-based approaches, such as data collected from public natural history platforms like iNaturalist, can involve more people and cover a broader geographic area. Few efforts have been made to quantify the pros and cons of these different approaches. We established a community science monitoring program to assess bee biodiversity across the state of Pennsylvania (USA) using specimen collections with nets, blue vane traps, and bowl traps. We recruited 26 participants, mostly Master Gardeners, from across the state to sample bees after receiving extensive training on bee monitoring topics and methods. The specimens they collected were identified to species, stored in museum collections, and the data added to public databases. Then, we compared the results from our collections to research-grade observations from iNaturalist during the same time period (2021 and 2022). At state and county levels, we found collections data documented over twice as much biodiversity and novel baseline natural history data (state and county records) than data from iNaturalist. iNaturalist data showed strong biases toward large-bodied and non-native species. This study demonstrates the value of highly trained community scientists for collections-based research that aims to document patterns of bee biodiversity over space and time.

Can citizen science inform science? Evaluating the results of the Bellingen Riverwatch citizen science program and a complimentary government monitoring program

In 2015, the sudden decline in the only known population of Myuchelys georgesi (the Bellinger River snapping turtle) triggered a strong community response, and a link between turtle mortality and poor water quality in the Bellinger River was suggested. A multi-agency investigation later attributed the mortalities of M. georgesi to a novel virus (the Bellinger River virus) and not a direct effect of poor water quality. However, a lack of consistent water quality or river health data in the catchment limited the research of factors that may have heightened susceptibility to the virus or exacerbated its symptoms. Community consultation identified strong connections with the riverine environment and highlighted the cultural, social, economic, and environmental values of the Bellinger River catchment. In 2017 OzGREEN, a not-for-profit environmental education charity based in Bellingen, built upon their existing citizen science water quality monitoring program in collaboration with the Saving our Species (SoS) team in the New South Wales (NSW) Department of Planning and Environment (DPE), who provided funding and equipment and solicited the involvement of NSW Waterwatch, Western Sydney University and Taronga Zoo. Now known as Bellingen Riverwatch (Riverwatch), the program has become a long-term citizen science program that aims to assist the recovery of M. georgesi, now a critically endangered species, through the delivery of monthly water quality data covering the Bellinger River and its tributaries. SoS also engaged the DPE Estuaries and Catchments Team to commence the Bellinger River Health Program (BRHP), focusing on water quality and aquatic macroinvertebrates to assess river health, with the aim of providing scientifically rigorous data to support the management and recovery of M. georgesi. This case study compares and evaluates the Riverwatch citizen science and the BRHP professional science, examining methods and results to compare the accuracy of the citizen science data and assess its reliability for informing ongoing river management. The results demonstrate that Bellingen Riverwatch is a well-managed citizen science program and generally provides valid, accurate, and representative results that can be confidently used to enhance the spatial and temporal coverage of the professional science monitoring program.

Long-term trends of local bird populations based on monitoring schemes: are they suitable for justifying management measures?

Local biodiversity monitoring is important to assess the effects of global change, but also to evaluate the performance of landscape and wildlife protection, since large-scale assessments may buffer local fluctuations, rare species tend to be underrepresented, and management actions are usually implemented on local scales. We estimated population trends of 58 bird species using open-population N-mixture models based on count data in two localities in southeastern Spain, which have been collected according to a citizen science monitoring program (SACRE, Monitoring Common Breeding Birds in Spain) over 21 and 15 years, respectively. We performed different abundance models for each species and study area, accounting for imperfect detection of individuals in replicated counts. After selecting the best models for each species and study area, empirical Bayes methods were used for estimating abundances, which allowed us to calculate population growth rates (λ) and finally population trends. We also compared the two local population trends and related them with national and European trends, and species functional traits (phenological status, dietary, and habitat specialization characteristics). Our results showed increasing trends for most species, but a weak correlation between populations of the same species from both study areas. In general, local population trends were consistent with the trends observed at national and continental scales, although contrasting patterns exist for several species, mainly with increasing local trends and decreasing Spanish and European trends. Moreover, we found no evidence of a relationship between population trends and species traits. We conclude that using open-population N-mixture models is an appropriate method to estimate population trends, and that citizen science-based monitoring schemes can be a source of data for such analyses. This modeling approach can help managers to assess the effectiveness of their actions at the local level in the context of global change.

Community science to the rescue: capturing water quality data during the COVID-19 pandemic

In 2020, the COVID-19 pandemic interrupted all aspects of human activity, including environmental research and monitoring. Despite a lack of laboratory access and other restrictive measures, we adapted an existing community science monitoring program to continue through the summer of 2020. We worked with local community groups to recruit 58 volunteers who collected lake water samples from 60 sites on 16 lakes in south-central Ontario from June to September 2020. We organized drop-off depots and had volunteers freeze samples to monitor nearshore nutrients (phosphorus and nitrogen) and chlorophyll-a. A survey was distributed to volunteers to analyze lake-front property owners’ activities during the pandemic. We found spatial patterns in nearshore water quality across the lakes, with sub-watershed development being a significant predictor of nutrients and chlorophyll-a. Additionally, pre-pandemic (2019) and pandemic (2020 and 2021) nutrient concentrations were compared, but there was no clear impact of the pandemic on nearshore nutrient concentrations, despite changes in lake-front property owners activities. Overall, this study demonstrated the ability of community science to provide water quality data on a large spatial scale despite a major societal disruption, providing insight into regional nutrient trends during the first year of the pandemic.

A GLMM approach for combining multiple relative abundance surfaces

Abstract Spatio‐temporal maps of organismal density or relative abundance are fundamental to many applications in conservation and ecology. There are often a number of data sources to inform species maps, including citizen science monitoring programs, remote sensing, geolocation data from satellite‐tagged animals and formal scientific surveys. In these cases, it may be desirable to come up with a single map integrating all data sources. We introduce a novel two‐step method for combining inference about relative abundance maps using multiple data sources. Log‐scale relative abundance surfaces are first estimated from individual data sets, and resultant surfaces are then treated as ‘data’ within a generalized linear mixed model framework with a spatially autocorrelated mean process. We also introduce generalizations allowing data misalignment and predictive processes to decrease computational burden. Using simulation, we show that our approach frequently outperfoms other approaches, including basing inference on a single surface, or taking a simple arithmetic mean (although the arithmetic mean performs well when there are few surfaces). We then demonstrate our method using citizen science and satellite‐tracking data of Steller sea lions in Alaska. In this case, relative abundance surfaces consisted of an effort‐adjusted map developed from platform‐of‐opportunity sightings and a utilization distribution developed from geolocation records. The resulting combined surface represented a compromise between single‐data source predictions. Our approach should be useful for ecologists seeking to reconcile alternative species distribution maps, particularly when individual surfaces are prone to bias, when there is no obvious common currency (e.g. point process), or when computational demands preclude a fully integrated analysis.

How to Include Crowd-Sourced Photogrammetry in a Geohazard Observatory—Case Study of the Giant’s Causeway Coastal Cliffs

The Causeway Coast World Heritage Site (Northern Ireland) is subject to rockfalls occurring on the coastal cliffs, thus raising major safety concerns given the number of tourists visiting the site. However, such high tourist frequentation makes this site favorable to implement citizen science monitoring programs. Besides allowing for the collection of a larger volume of data, better distributed spatially and temporally, citizen science also increases citizens’ awareness—in this case, about risks. Among citizen science approaches, Structure-from-Motion photogrammetry based on crowd-sourced photographs has the advantage of not requiring any particular expertise on the part of the operator who takes photos. Using a mock citizen survey for testing purposes, this study evaluated different methods relying on crowd-sourced photogrammetry to integrate surveys performed by citizens into a landslide monitoring program in Port Ganny (part of the touristic site of the Giant’s Causeway). Among the processing scenarios that were tested, the Time-SIFT method allows the use of crowd-sourced data in a very satisfactory way in terms of reconstruction quality, with a standard deviation of 8.6 cm.

Engaging Online Citizen Scientists and the Consensus Method to Monitor the Marine Biofouling Community

Citizen science is an important and useful approach to research that broadens public science engagement and expands the scale at which science can be conducted. Monitoring for marine non-native species has been repeatedly identified as a venue for citizen scientists to make substantial contributions. In this study, we evaluated the accuracy of identifications made by volunteers of marine invertebrates on the project Invader ID, hosted on the online citizen science portal Zooniverse. We tested the efficiency and accuracy of invertebrate identifications made through consensus, where more than one volunteer must agree on a final identification before it is added to the database. Using the Matthew’s Correlation Coefficient, we found that four volunteers in consensus balanced efficiency and accuracy when compared to gold standard scientist identifications. Common, large taxa were identified most accurately; Branching Bryozoa identifications made by four volunteers were 85% accurate, Solitary Tunicates 91% accurate, and Colonial Tunicates 64%. In community-based comparisons, the identity of the taxonomist (volunteer or scientist) had a small impact on overall community composition, while site and salinity gradients had a strong impact on composition. We suggest that citizen science monitoring programs focused on highly recognizable taxonomic groups, or on a few species within those groups that can provide crucial information for managers aiming to quickly identify new invasions. Moreover, long-term assessments of composition could be successfully monitored by volunteers from photographs, helping to bolster understanding of ongoing impacts of invasive species or climate change.

Bio-Ethology of Vespa crabro in Sardinia (Italy), an Area of New Introduction.

Simple SummaryAlien insects, including hornets, may show invasive traits in non-native areas, thus threatening the ecological balance of natural and agro-ecosystems. The European hornet, Vespa crabro, is an omnivorous eusocial insect predator of many arthropods, including honey bees. It is native to Eurasia and established in Sardinia (Italy) in 2010, where it is an alien species. Vespa crabro does not represent a danger for beekeeping in its native area, although the potential environmental impacts in non-native areas are unknown. In view of the lack of such studies, this research investigated the potential invasive traits of V. crabro in an area of new introduction, with special regard to predatory activity against honey bees. Observations of hornet foraging behaviour in open fields highlighted a prevalent foraging activity on fruits and no preference for bees compared to other recognizable arthropods. Furthermore, behavioural and predatory observations of V. crabro near apiaries showed that foragers returned to nests carrying preys in 1% of cases. Vespa crabro did not show invasive traits nor notable behavioural changes in a non-native compared to its native area, as the hornet was confirmed to be a mild predator of honey bees. Therefore, the European hornet is not likely to represent a threat to beekeeping in Sardinia.Vespa crabro, also known as European hornet, is a eusocial Vespidae originally from Eurasia that was accidentally introduced on the island of Sardinia (Italy) in 2010. Currently, its distribution is limited to the northern area of the island. Considering that a non-harmful species in its native region can exhibit invasive behaviour when established in new environments, bio-ethological observations were conducted to better understand whether V. crabro could show invasive traits in Sardinia, which represents a new introduction area. Data on the foraging activity of the European hornet in open fields were collected within a citizen science monitoring program carried out in Sardinia from 2018 to 2020. Moreover, specific behavioural observations were made in apiaries to assess the predatory activity of the hornet towards honey bees and at the entrance of free-living European hornet colonies to evaluate other aspects of its behaviour, i.e., intranidal and extranidal tasks. The results of our study are discussed in relation to the behavioural traits known for this species in its native areas to place the behavioural repertoire of V. crabro in Sardinia into a wider context. Our observations revealed that V. crabro did not show any changes in behavioural traits in Sardinia compared to those described in its area of origin, so the risk of becoming an invasive species on this island seems unlikely.

Fish Love Floods: Benefits of Floodplains in San Francisco Estuary

Lots of rain can make rivers rise, causing them to spill into low-lying areas called floodplains. Floodplains protect cities from flooding and provide food-rich, safe habitats for freshwater creatures. The largest floodplain of the San Francisco Estuary is the Yolo Bypass. The Yolo Bypass is connected to the Sacramento River and protects Sacramento and surrounding areas from flooding. A twenty-plus year scientific monitoring program in the Yolo Bypass has documented many benefits that this floodplain provides to the Estuary. For example, the Yolo Bypass is a nursery area for baby fish such as young Chinook salmon and Sacramento splittail, and it is an important food bank that transports fish food to the rest of the Estuary. This article discusses some of the benefits that floodplains provide for fish species, and it highlights the importance of long-term monitoring to help scientists and managers make decisions for the benefit of fishes and ecosystems.

Initial insights into the development and implementation of a citizen-science drone-based coastal change monitoring program in the Great Lakes region

High-resolution spatio-temporal data are needed to improve coastal management programs, particularly along the Great Lakes where lake level fluctuations pose challenges to coastal decision-making and planning. Unfortunately, there is a paucity of coastal change monitoring datasets, particularly those that document event-scale changes over a large spatial scale. This paucity of data is compounded by the large size and range of shore types throughout the region.Unoccupied aerial vehicle (UAV) or drone data collected by citizen scientists are a potential solution to this challenge. However, no citizen science coastal change monitoring program exists in the Great Lakes region, nor does a comprehensive drone-based coastal change monitoring programs exist anywhere in the United States. To inform the development of drone-based citizen science programs, the goal of this paper is to describe the development and implementation of a citizen science coastal change monitoring program along the Great Lakes shores of Michigan. The citizens participating in this project generate imagery in two ways: (1) the submission of photos of coastal changes or hazards via a web app developed for the project called PicShores and (2) drone collection of survey-quality aerial imagery for use in the generation of orthomosaic images and digital elevation models (DEMs). This paper presents the methods utilized to develop the citizen science monitoring program, some initial findings from the citizen science monitoring, and explores some challenges and next steps for the program.

Motivation and support services in citizen science insect monitoring: A cross-country study

The design and successful performance of citizen science-based monitoring require an understanding of the motivation and the needs of participants. Herem we use a questionnaire to assess intrinsic and extrinsic motivations and investigate in links between project support service and motivations in 181 participants taking part in three insect-focused citizen science projects in Denmark, Germany and Israel. Across all three countries, main intrinsic motivation for participating in the projects were “to have fun” and to “do something (good) for nature”. Equally important across all countries were extrinsic motivations such as “contribute to science” and “contribute to nature conservation”. Interestingly, differences in the projects (country or program-type) were more strongly related to respondent's motivation than demographic variables such as age and gender. Linking project support services to participants' intrinsic and extrinsic motivations revealed that the intrinsic motivation of “feeling a part of the community” as well as the extrinsic motivation “learning” and the service to provide “training on insect identification” were positively related. Interestingly, the support service of “monetary incentives” was negatively related with the motivation to “conserve species generally” and “conserve insects specifically”. We conclude, that early identification of the citizen scientists' motivation and the assessment of how motivations may change over time are important to foster successful and sustainable citizen science monitoring programs. International networks of (potentially similar) biodiversity monitoring schemes should consider differences in cultural background and citizen scientist's requirements, and accordingly tailor the projects designs to activate, train, and support participants according to their needs.

Influence of the COVID-19 pandemic on amphibian road mortality.

The COVID‐19 pandemic and its related human activity shutdowns provide unique opportunities for biodiversity monitoring through what has been termed the “anthropause” or the “great human confinement experiment.” The pandemic caused immense disruption to human activity in the northeastern United States in the spring of 2020, with notable reductions in traffic levels. These shutdowns coincided with the seasonal migration of adult amphibians, which are typically subject to intense vehicle‐impact mortality. Using data collected as part of an annual community science monitoring program in Maine from 2018 to 2021, we examined how amphibian mortality probabilities responded to reductions in traffic during the pandemic. While we detected a 50% decline for all amphibians, this was driven entirely by reductions in frog mortality. Wildlife collision data from the Maine Department of Transportation on other wildlife species support our finding of drastic declines in wildlife road mortality in spring 2020 when compared with immediately previous and subsequent years. Additionally, we find that frogs suffer significantly higher road mortality than salamanders, particularly when conditions are warmer and wetter.

Harnessing scientific and local knowledge to face climate change in small-scale fisheries

Small-scale fisheries in developing regions are particularly vulnerable to climate change, but the assessment of climate-induced changes and impacts are often hampered by the data poor-situation of these social-ecological systems. Based on 40 years of scientific and local ecological knowledge, we provide a coherent narrative about the effects of a marine hotspot of climate change on a small-scale fishery across different geographical and temporal scales. We applied a mixed-methods approach to assess biophysical changes, social-ecological impacts, and the incremental spectrum of actions implemented at multiple levels to increase the adaptive capacity of a small-scale clam fishery. The warming hotspot here analyzed was the fastest-warming region in the South Atlantic Ocean. Long-term changes in wind intensity and direction were also noticeable at a regional scale. Both sea surface temperature and winds showed a clear shifting pattern in the late 1990 s. These climate-related stressors determined ecosystem and targeted population changes (e.g. clam mass mortalities, slow stock recovery rates after ecological shocks, habitat narrowing), and favored harmful algal bloom-forming organisms. Climate-induced drivers also affected the human component of the social-ecological system, preventing fishers from securing a fulltime livelihood and limiting the fishery economic potential. Adaptive responses at multiple levels provided some capacity to address climate change effects, and transformative pathways are being taken to adapt to climate-induced changes over the long-term. Transformative changes were fostered by the local perception of environmental change, shared narratives, sustained scientific monitoring programs, and the interaction between knowledge systems, facilitated by a bridging organization within a broader process of governance transformation. The combination of autonomous adaptations (based on linking social capital and fishery leaders agency) and government-led adaptations were essential to face the challenges imposed by climate change. Our results serve as a learning platform to anticipate threats and envision solutions to a wide range of small-scale fisheries in fast-warming regions worldwide.

Koala Counter: Recording Citizen Scientists’ search paths to Improve Data Quality

Biodiversity monitoring is key for developing informed solutions to the threats facing our environment, including habitat loss, increasing pollution, wildlife trafficking and climate change. Citizen science is increasingly used for collecting species observational data at wide spatial and temporal scales that are difficult and expensive to achieve using traditional means. Current apps used for citizen science biodiversity monitoring provide methods to record observational data on species’ presence, including photos, location, date, time and an assortment of other data. However, data about species absences as well as automatically generated and accurate data on both search effort and search locations have been lacking. Koala Counter is a free, cross-platform (Android & iOS), open-source app that was developed for a citizen science project to collect koala population data to inform koala conservation and management in South Australia. The app uses mobile phone sensors to transparently and automatically record metadata such as species observation location and time, the search path the user takes, the time taken while searching and GPS location precision. We tested this in the Citizen Science event “The Great Koala Count 2” in South Australia during November 2016. Observations, paths and search effort data were accurate overall. Location accuracy was good, with some exceptions. Use of the app indicated a number of potential improvements that would further increase data quality. Recording search paths offers a potentially valuable method of recording spatial and temporal components of search effort, improving on simple records of species observations and time taken, especially when no observations are made. These data may enable better ecological modelling by supplying accurate search effort data as well as enabling improved inference of species absence. Search paths also show locations that have not been searched, which is valuable information in management of citizen science monitoring programs.

Dispersal patterns of an introduced wild bee, Megachile sculpturalis Smith, 1853 (Hymenoptera: Megachilidae) in European alpine countries.

Biodiversity monitoring programs are the baseline of species abundancy studies, which in case of introduced species are especially critical. Megachile sculpturalis Smith, 1853 native to Eastern-Asia, constitutes the first ever recorded wild bee species accidently introduced in Europe. Since its first discovery in 2008, M. sculpturalis has been spreading across the continent. By initiating a citizen science monitoring program, we aimed to investigate the occurrence pattern of M. sculpturalis. Within only two years after starting the project, 111 new reports from Switzerland, Liechtenstein and Austria were recorded. Comparably to other European countries, the population progressed remarkably fast from year to year expanding its area geographically but also ecologically by increasing its altitudinal range. The distribution pattern indicates human assisted jump-dispersal travelling on the major traffic routes of central Europe.

The Importance of Connected Ocean Monitoring Knowledge Systems and Communities

Ocean monitoring will improve outcomes if ways of knowing and priorities from a range of interest groups are successfully integrated. Coastal Indigenous communities hold unique knowledge of the ocean gathered through many generations of inter-dependent living with marine ecosystems. Experiences and observations from living within that system have generated ongoing local and traditional ecological knowledge (LEK and TEK) and Indigenous knowledge (IK) upon which localized sustainable management strategies have been based. Consequently, a comprehensive approach to ocean monitoring should connect academic practices (‘science’) and local community and Indigenous practices, encompassing ‘TEK, LEK and IK.’ This paper recommends research approaches and methods for connecting scientists, local communities and IK holders and their respective knowledge systems, and priorities, to help improve marine ecosystem management. Case studies from Canada and New Zealand (NZ) highlight the emerging recognition of IK systems in natural resource management, policy and economic development. The in-depth case studies from Ocean Networks Canada (ONC) and the new Moana Project, NZ highlight real-world experiences connecting IK with scientific monitoring programs. Trial-tested recommendations for successful collaboration include practices for two-way knowledge sharing between scientists and communities, co-development of funding proposals, project plans and educational resources, mutually agreed installation of monitoring equipment, and ongoing sharing of data and research results. We recommend that future ocean monitoring research be conducted using cross-cultural and/or transdisciplinary approaches. Vast oceans and relatively limited monitoring data coupled with the urgency of a changing climate emphasize the need for all eyes possible providing new data and insights. Community members and ocean monitoring scientists in joint research teams are essential for increasing ocean information using diverse methods compared with previous scientific research. Research partnerships can also ensure impactful outcomes through improved understanding of community needs and priorities.

Quantifying data quality in a citizen science monitoring program: False negatives, false positives and occupancy trends

AbstractData collected by volunteers are an important source of information used in species management decisions, yet concerns are often raised over the quality of such data. Two major forms of error exist in occupancy datasets; failing to observe a species when present (imperfect detection—also known as false negatives), and falsely reporting a species as present (false‐positive errors). Estimating these rates allows us to quantify volunteer data quality, and may prevent the inference of erroneous trends. We use a new parameterization of a dynamic occupancy model to estimate and adjust for false‐negative and false‐positive errors, producing accurate estimates of occupancy. We validated this model using simulations and applied it to 12 species datasets collected from a 15‐year, large‐scale volunteer amphibian monitoring program. False‐positive rates were low for most, but not all, species, and accounting for these errors led to quantitative differences in occupancy, although trends remained consistent even when these effects were ignored. We present a model that represents an intuitive way of quantifying the quality of volunteer monitoring datasets, and which can produce unbiased estimates of occupancy despite the presence of multiple types of observation error. Importantly, this allows the quality of volunteer monitoring data to be assessed without relying on comparisons with expert data.