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.

Although the quality of citizen science (CS) data is often a concern, evidence for high-quality CS data increases in the scientific literature. This study aimed to assess the data reliability of a structured CS protocol for monitoring stingless bees’ flight activity. We tested (1) data accuracy for replication among volunteers and for expert validation and (2) precision, comparing dispersion between citizen scientists and expert data. Two distinct activity dimensions were considered: (a) perception of flight activity and (b) flight activity counts (entrances, exits, and pollen load). No significant differences were found among groups regarding entrances and exits. However, replicator citizen scientists presented a higher chance of perceiving pollen than original data collectors and experts, likely a false positive. For those videos in which there was an agreement about pollen presence, the effective pollen counts were similar (with higher dispersion for citizen scientists), indicating the reliability of CS-collected data. The quality of the videos, a potential source of variance, did not influence the results. Increasing practical training could be an alternative to improve pollen data quality. Our study shows that CS provides reliable data for monitoring bee activity and highlights the relevance of a multi-dimensional approach for assessing CS data quality.

The implementation of Citizen Science in biodiversity studies has led the general public to engage in environmental actions and to contribute to the conservation of natural resources (Chandler et al. 2017). Smartphones have become part of the daily lives of millions of people, allowing the general public to collect data and conduct automatic measurements at a very low cost. Indeed, a series of Citizen Science mobile applications have allowed citizens to rapidly record specimen observations and contribute for the development of large biodiversity databases around the World. Citizen Science applications have a multitude of purposes, as well as target a variety of taxa, biological questions and geographical regions. Brazil is a megadiverse country that includes many threatened species and Biomes. Conversation efforts are urgent and the engagement of the civil society is critical. Brazilian dry and wet forests are dominated by members of the plant family Bignoniaceae, all of which are characterized by beautiful trumpet-shaped flowers and a big-bang flowering strategy. Species of the Neotropical Bignoniaceae trees are popularly known in Brazil as “Ipê” and are broadly cultivated throughout the country due to the showy flowers and strong wood. Different species have different flower colors, making its identification relatively easy. The showy and colorful flowers are extremely admired by the local population and the media. Flowering of “Ipês” is triggered by dry climate, lower temperatures and increasing day-light, making this group an excellent model for phenological and climatic studies involving Citizen Science. Here, we developed a multi-platform mobile application focused on the plant family Bignoniaceae that allows users to contribute phenological data for species from this plant family. More specifically, through this application the user is able to provide data about specimen locations, phenology and date, all of which can be validated by a photograph. This platform is based on React Native, a hybrid app framework that helps the developers to reuse the code across multiple mobile platforms, a development much more efficient and with efforts focused on the user experience. This technology uses Javascript as programming language and Facebook React as a basis for development. The system is similar to other CS apps such as iNaturalist. Namely, the overall observations improve the quality of the ranking through positive feedback from the community, strengthening the network of interactions between users and encouraging active participation. On the other hand, the application allows users to access all previously stored observations, which, in turn, can suggest improvements to that particular observation. Furthermore, observations without a correct ID can be stored until others can suggest a correct identification, maximizing the value of individual observations and data gathered. An important aspect of this mobile application is the participation of a network of experts on this plant family, allowing a rapid and accurate verification of individual observations. This team of Bignoniaceae experts is also able to make full use of the data gathered by correlating climate and phenological patterns. Results from these analyses are provided to the citizens gathering the data which will, in turn, stimulate the collection of new data, especially in poorly sampled locations. This is a very dynamic mobile application, that aims to engage the civil society with true scientific research, stimulating the management of natural resources and conservation efforts. Through this mobile app, we hope to engage the general public into biodiversity studies by improving their knowledge on an iconic group of Brazilian plants, while contributing data for scientific studies. The system is expected to be released in May and will be available at ipesdobrasil.org.br.

Para mensurar a qualidade do biodiesel no Brasil, vários parâmetros são estabelecidos. Alguns deles como viscosidade, índice de iodo, número de cetano, densidade são importantes pois caracterizam funções importantes de como o biodiesel irá reagir no motores. Neste estudo, foram usadas Redes Neurais Artificiais (RNAs) para predizer o índice de viscosidade do biodiesel. Para este fim foram utilizadas 13 compostos de esteres deácidos graxos como entrada para as RNAs, com vários algoritmos de convergência do tipo feedforward tendo como sáıda das redes os índices de viscosidade.