Citizen science improves our understanding of the impact of soil management on wild pollinator abundance in agroecosystems

Farmland biodiversity monitoring through citizen science: A review of existing approaches and future opportunities

Biodiversity monitoring in agricultural landscapes is important for assessing the effects of both land use change and activities that influence farmland biodiversity. Despite a considerable increase in citizen science approaches to biodiversity monitoring in recent decades, their potential in farmland-specific contexts has not been systematically examined. This paper therefore provides a comprehensive review of existing citizen science approaches involving biodiversity monitoring on farmland. Using three complementary methods, we identify a range of programmes at least partially covering farmland. From these, we develop a typology of eight programme types, reflecting distinctions in types of data collected and nature of volunteer involvement, and highlight their respective strengths and limitations. While all eight types can make substantial contributions to farmland biodiversity monitoring, there is considerable scope for their further development-particularly through increased engagement of farmers, for whom receiving feedback on the effects of their own practices could help facilitate adaptive management.

Determining Minnesota bee species' distributions and phenologies with the help of participatory science

The Minnesota Bee Atlas project contributed new information about bee distributions, phenologies, and community structure by mobilizing participatory science volunteers to document bees statewide. Volunteers submitted iNaturalist (©2016 California Academy of Sciences) photograph observations, monitored nest-traps for tunnel-nesting bees, and conducted roadside observational bumble bee surveys. By pairing research scientists and participatory science volunteers, we overcame geographic and temporal challenges to document the presence, phenologies, and abundances of species. Minnesota Bee Atlas project observations included new state records for Megachile inimica, Megachile frugalis, Megachile sculpturalis, Osmia georgica, Stelis permaculata, and Bombus nevadensis, nesting phenology for 17 species, a new documentation of bivoltinism for Megachile relativa in Minnesota, and over 500 observations of the endangered species Bombus affinis. We also expanded known ranges for 16 bee species compared with specimens available from the University of Minnesota (UMN) Insect Collection. Surveys with standardized effort across the state found ecological province associations for six tunnel-nesting species and lower bumble bee abundance in the Prairie Parkland ecological province than the Laurentian Mixed Forest or Eastern Broadleaf Forest ecological provinces, indicating potential benefit of a focus on bumble bee habitat management in the Prairie Parkland. Landcover analysis found associations for four tunnel-nesting species, as well as a possible association of B. affinis with developed areas. These data can inform management decisions affecting pollinator conservation and recovery of endangered species. By engaging over 2,500 project volunteers and other iNaturalist users, we also promoted conservation action for pollinators through our educational programs and interactions.

The Eyewitness Community Survey: An Engaging Citizen Science Tool to Capture Reliable Data while Improving Community Participants' Environmental Health Knowledge and Attitudes

Many youths and young adults have variable environmental health knowledge, limited understanding of their local environment's impact on their health, and poor environmentally friendly behaviors. We sought to develop and test a tool to reliably capture data, increase environmental health knowledge, and engage youths as citizen scientists to examine and take action on their community's challenges. The Eyewitness Community Survey (ECS) was developed through several iterations of co-design. Herein, we tested its performance. In Phase I, seven youths audited five 360° photographs. In Phase II, 27 participants works as pairs/trios and audited five locations, typically 7 days apart. Inter-rater and intra-rater reliability were determined. Changes in participants' knowledge, attitudes, behaviors, and self-efficacy were surveyed. Feedback was obtained via focus groups. Intra-rater reliability was in the substantial/near-perfect range, with Phase II having greater consistency. Inter-rater reliability was high, with 42% and 63% of Phase I and II Kappa, respectively, in the substantial/near-perfect range. Knowledge scores improved after making observations (p ≤ 0.032). Participants (85%) reported the tool to be easy/very easy to use, with 70% willing to use it again. Thus, the ECS is a mutually beneficial citizen science tool that rigorously captures environmental data and provides engaging experiential learning opportunities.

A Critical Review for Real-Time Continuous Soil Monitoring: Advantages, Challenges, and Perspectives

Most soil quality measurements have been limited to laboratory-based methods that suffer from time delay, high cost, intensive labor requirement, discrete data collection, and tedious sample pretreatment. Real-time continuous soil monitoring (RTCSM) possesses a great potential to revolutionize field measurements by providing first-hand information for continuously tracking variations of heterogeneous soil parameters and diverse pollutants in a timely manner and thus enable constant updates essential for system control and decision-making. Through a systematic literature search and comprehensive analysis of state-of-the-art RTCSM technologies, extensive discussion of their vital hurdles, and sharing of our future perspectives, this critical review bridges the knowledge gap of spatiotemporal uninterrupted soil monitoring and soil management execution. First, the barriers for reliable RTCSM data acquisition are elucidated by examining typical soil monitoring techniques (e.g., electrochemical and spectroscopic sensors). Next, the prevailing challenges of the RTCSM sensor network, data transmission, data processing, and personalized data management are comprehensively discussed. Furthermore, this review explores RTCSM data application for updating diverse strategies including high-fidelity soil process models, control methodologies, digital soil mapping, soil degradation, food security, and climate change mitigation. Finally, the significance of RTCSM implementation in agricultural and environmental fields is underscored through illuminating future directions and perspectives in this systematic review.

Beewatching: A Project for Monitoring Bees through Photos

Bees play a key role in natural and agro-ecosystems and their diversity is worldwide threatened by anthropogenic causes. Despite this, there is little awareness of the existence of the numerous species of wild bees, and the common name "bee" is very often exclusively associated with Apis mellifera. Our aim was to create a citizen science project in Italy with the following objectives: (a) raising awareness of the importance and diversity of bees, (b) obtaining data on the biology, ecology and distribution of Italian species, and (c) launching the monitoring of alien bees. The first step of the project was to create a website platform with a section containing informative datasheets of the wild bee families and of the most common bee genera present in Italy, a form to send reports of observed bees and an interactive map with all citizen's reports. During the 2 years of the project 1086 reports were sent by 269 users, with 38 Apoidea genera reported on 190 plant genera; furthermore, 22 reports regarding the alien species Megachile sculpturalis arrived. The majority of bees (34 genera) were observed on spontaneous plants, including 115 genera native to Italy. Considering the increasing number of reports and data obtained in these first two years of the project, our objectives seem to be achieved. Future steps will be to outline the profile of beewatchers, to plan activities in a more targeted way, and also to start some sub-projects for conservation purposes.

Fascination and Joy: Emotions Predict Urban Gardeners' Pro-Pollinator Behaviour

Simple Summary

The protection of pollinating insects depends on public support. Citizen science (CS) is frequently discussed as a way to promote interest and conservation action for pollinators. In cities, the drivers behind pollinator-friendly behaviour are largely unclear. We surveyed 111 community gardeners in Berlin and Munich, Germany, some of which were participating in a citizen science project. We created four different sets of generalized linear models to analyse how the gardeners’ pro-pollinator behaviour intentions and behaviour were explained by the gardener’s identity, emotions towards pollinators, attitudes towards pollinators and nature-relatedness. Respondents who were fascinated by pollinators, held positive attitudes, and felt joy about seeing pollinators reported intentions to protect or support pollinators. Similarly, joy about seeing pollinators was a predictor of participation in the CS project. We believe that CS may represent a pathway through which urban residents may become key actors in conservation projects within their nearby greenspaces.

Abstract

The conservation of pollinators requires social understanding to catalyse restoration action. Citizen science (CS) is discussed as a way to promote interest and action for pollinating insects. Yet, the drivers behind pro-pollinator behaviour are largely unclear, especially in urban areas. To better understand public engagement in pollinator conservation, we studied urban community gardeners’ identity, nature-relatedness, emotions, and attitudes toward pollinators and their intentions to get involved in pro-pollinator behaviour in their gardening practice. We surveyed community gardeners in Berlin and Munich, Germany, some of which were participating in a citizen science project. In this scientific study, we created four different sets of generalized linear models to analyse how the gardeners’ pro-pollinator behaviour intentions and behaviour were explained by socio-psychological factors. The responses of 111 gardeners revealed that gardeners that were fascinated by pollinators, held positive attitudes and felt joy about seeing pollinators reported intentions to protect or support pollinators, suggesting that fascination and joy can be harnessed for research and conservation on pollinators. Similarly, joy about seeing pollinators predicted participation in the CS project. We believe that CS may represent a pathway through which urban residents may become key actors in conservation projects within their nearby greenspaces.

Hoary Squash Bees (Eucera pruinosa: Hymenoptera: Apidae) Provide Abundant and Reliable Pollination Services to Cucurbita Crops in Ontario (Canada)

The increasing demand for insect-pollinated crops highlights the need for crop pollination paradigms that include all available pollinators. In North America, Cucurbita crops (pumpkin, squash) depend on both wild (solitary and Bombus spp.: Hymenoptera: Apidae) and managed honey bees (Apis mellifera L. 1758: Hymenoptera: Apidae) for pollination. Temporal and spatial differences in abundance may determine which bee taxa are the most important pollinators of Cucurbita crops. We surveyed bees visiting Cucurbita crop flowers on 19 farms over four years (2015-2018) during the crop flowering period (July 1-August 30 from 06:00-12:00). All the farms surveyed had hoary squash bees (Eucera pruinosa (Say, 1867), and most also had some combination of honey bees, bumble bees (Bombus spp.), or other wild bees present on their Cucurbita crop flowers. All four bee taxa were present on about two-thirds of farms. Spatially and temporally, wild bees were more abundant on Cucurbita crop flowers than managed honey bees. Hoary squash bees were the most abundant wild bees, maintaining their abundance relative to other wild bee taxa year-over-year. Male hoary squash bees were both more frequently and consistently seen visiting crop flowers than females in all years. Peak activity of hoary squash bees and bumble bees coincided with the daily crop pollination window, whereas peak activity of honey bees and other wild bees occurred after that window. In addition to elucidating the ecological interactions among wild and managed pollinators on Cucurbita crops, our work provides a novel practical way to evaluate pollinator abundance using a crop-centered benchmark framework.

A Buzz for Sustainability and Conservation: The Growing Potential of Citizen Science Studies on Bees

Expanding involvement of the public in citizen science projects can benefit both volunteers and professional scientists alike. Recently, citizen science has come into focus as an important data source for reporting and monitoring United Nations Sustainable Development Goals (SDGs). Since bees play an essential role in the pollination ecosystem service, citizen science projects involving them have a high potential for attaining SDGs. By performing a systematic review of citizen science studies on bees, we assessed how these studies could contribute towards SDG reporting and monitoring, and also verified compliance with citizen science principles. Eighty eight studies published from 1992 to 2020 were collected. SDG 15 (Life on Land) and SDG 17 (Partnerships) were the most outstanding, potentially contributing to targets related to biodiversity protection, restoration and sustainable use, capacity building and establishing multi stakeholder partnerships. SDG 2 (Zero Hunger), SDG 4 (Quality Education), and SDG 11 (Sustainable Cities and Communities) were also addressed. Studies were found to produce new knowledge, apply methods to improve data quality, and invest in open access publishing. Notably, volunteer participation was mainly restricted to data collection. Further challenges include extending these initiatives to developing countries, where only a few citizen science projects are underway.

Nutrient Diagnosis of Fertigated "Prata" and "Cavendish" Banana (Musa spp.) at Plot-Scale

Fertigation management of banana plantations at a plot scale is expanding rapidly in Brazil. To guide nutrient management at such a small scale, genetic, environmental and managerial features should be well understood. Machine learning and compositional data analysis (CoDa) methods can measure the effects of feature combinations on banana yield and rank nutrients in the order of their limitation. Our objectives are to review ML and CoDa models for application at regional and local scales, and to customize nutrient diagnoses of fertigated banana at the plot scale. We documented 940 "Prata" and "Cavendish" plot units for tissue and soil tests, environmental and managerial features, and fruit yield. A Neural Network informed by soil tests, tissue tests and other features was the most proficient learner (AUC up to 0.827). Tissue nutrients were shown to have the greatest impact on model accuracy. Regional nutrient standards were elaborated as centered log ratio means and standard deviations of high-yield and nutritionally balanced specimens. Plot-scale diagnosis was customized using the closest successful factor-specific tissue compositions identified by the smallest Euclidean distance from the diagnosed composition using centered or isometric log ratios. Nutrient imbalance differed between regional and plot-scale diagnoses, indicating the profound influence of local factors on plant nutrition. However, plot-scale diagnoses require large, reliable datasets to customize nutrient management using ML and CoDa models.