This supports the modelling communities and the development of ecosystem assessments and future scenarios supporting conservation mitigation strategies (Akçkaya et al. BONs obtain baseline data, develop monitoring programs to detect change, publish biodiversity observations, and help identify the factors underlying the observed changes. The aim of a BON is to help improve information available on the distribution and change of biodiversity in a given region or associated with a specific theme (e.g., an ecosystem domain or a particular type of monitoring) (GEO BON 2015a, b). All are important issues that determine whether useable data are collected and how a team of willing and capable participants is maintained.
2013), and the use of emerging technologies. 2014), participant recruitment and motivation (Buesching et al. To this end, this chapter also considers practical issues such as reliability of the data (Buesching et al. The design of successful monitoring or observation networks that rely on citizen observers requires a careful balancing of the two primary user groups, namely data users and data contributors (i.e., citizen scientists Pocock et al. Other forms of CS are also possible, such as through the Earthwatch model ( ) where members of the public join research projects these require more training, direction and supervision of participants to ensure systematic data collection for answering specific scientific research questions. ( 2012), involving citizens primarily in data collection is the most common form and probably the simplest starting point for those interested in developing new CS projects. Referred to as contributory CS, which is based on a typology developed by Bonney et al. This chapter provides examples of how CS can contribute to ongoing efforts in biodiversity monitoring, enhancing observation and recording of key species and systems in a standardised manner, and supporting the collection of Essential Biodiversity Variables (EBVs), as well as reaching key constituencies who would benefit Biodiversity Observation Networks (BONs). By achieving hitherto unrealised levels of large-scale monitoring for features which remain invisible to remote sensing, CS is likely the most realistic way of covering much of the planet’s biosphere (Pereira and Cooper 2006 Pereira et al.
With limited budgets to pay for professional scientists, or to support government-sponsored environmental monitoring, engaging citizens to help with ground-based monitoring efforts and the reporting of rare events, makes sense. With recent changes in technology and social media enabling outreach and interaction with a much wider audience than ever before, CS is becoming an increasingly integral part of contemporary scientific research, particularly in terms of data acquisition. Famous names such as Alfred Russell Wallace, Thomas Edison and Gregor Mendel are all prime historical examples of citizen scientists.
In the past, amateur scientists have contributed a great deal to science, particularly with networks of weather collectors and ocean monitoring. Although the term has appeared only more recently as a formal way of referring to these activities, CS actually has a very long history. The involvement of non-professionals in scientific research and environmental monitoring, termed Citizen Science (CS), has now become a mainstream approach for collecting data on earth processes, ecosystems and biodiversity.
To this end, this chapter identifies examples of successful CS programs as well as considering practical issues such as the reliability of the data, participant recruitment and motivation, and the use of emerging technologies. The design of successful monitoring or observation networks that rely on citizen observers requires a careful balancing of the two primary user groups, namely data users and data contributors (i.e., citizen scientists). This chapter examines how CS might contribute to ongoing efforts in biodiversity monitoring, enhancing observation and recording of key species and systems in a standardised manner, thereby supporting data relevant to the Essential Biodiversity Variables (EBVs), as well as reaching key constituencies who would benefit Biodiversity Observation Networks (BONs).