https://repository.oceanbestpractices.org/handle/11329/2415 2026-06-13T11:48:49Z 2026-06-13T11:48:49Z Bonicalza, Sofia Valsecchi, Elena Coppola, Emanuele Catapano, Valeria Thatcher, Harriet https://repository.oceanbestpractices.org/handle/11329/2627 2025-07-01T15:32:23Z 2024-01-01T00:00:00Z

Citizen science in eDNA monitoring for Mediterranean monk seal conservation. Bonicalza, Sofia; Valsecchi, Elena; Coppola, Emanuele; Catapano, Valeria; Thatcher, Harriet Background Citizen Science (CS) offers a promising approach to enhance data collection and engage communities in conservation efforts. This study evaluates the use of CS in environmental DNA (eDNA) monitoring for Mediterranean monk seal conservation. We validated CS by assessing the effectiveness of a newly developed CS-friendly filtration system called “WET” (Water eDNA Trap) in eDNA detection, addressing technical challenges, and analysing volunteer faults. The WET is a 4-litre, manual pump-based filtering system using positive pressure to force water through the filter. We also assessed the use of a retrospective questionnaire as a tool to measure CS’s social impact on participants’ perceived knowledge, attitudes, and conservation behaviours. Results Results suggest the WET performs comparably to traditional methods, with minor technical issues. Despite some faults such as not folding or forgetting to change the filter, volunteers were generally reliable in sample processing. Moreover, CS involvement increased participants’ perceived knowledge, affective attitudes, and conservation behaviours towards seal conservation. Volunteers reported a greater understanding of eDNA monitoring, increased interest in monk seal conservation, and more frequent conservation behaviours, including spreading awareness within their community. While these findings are exploratory due to the small sample size (19 participants) and potential ceiling effects in attitude assessment, they provide an initial validation of the questionnaire as a tool for measuring CS’s social outcomes. Future studies with larger sample sizes are needed to confirm these results and investigate their applicability across broader stakeholder groups. Continuous improvement in volunteer training and equipment design is also recommended. Conclusions This study highlights CS’s potential to improve public engagement and knowledge in conservation. By involving diverse participants, CS can play a critical role in long-term conservation efforts and promote sustainable coexistence between humans and monk seals. Furthermore, the validation of the questionnaire offers a valuable framework for evaluating the social impact of CS initiatives in conservation contexts.

2024-01-01T00:00:00Z Ceccaroni, Luigi Parkinson, Stephen Woods, Sasha Sprinks, James Wehn, Uta Scrieciu, Albert Kozak, Balaz Gumiero, Bruna Joyce, Hannah Naura, Marc Janes, Martin Williams, Claire https://repository.oceanbestpractices.org/handle/11329/2420 2024-01-17T19:32:34Z 2022-01-01T00:00:00Z

The impact of citizen science on society, governance, the economy, the environment and science. Ceccaroni, Luigi; Parkinson, Stephen; Woods, Sasha; Sprinks, James; Wehn, Uta; Scrieciu, Albert; Kozak, Balaz; Gumiero, Bruna; Joyce, Hannah; Naura, Marc; Janes, Martin; Williams, Claire The MICS project [mics.tools] has developed a state-of-the-art tool for assessing citizen science’s impact. The free-to-use, open-access platform is available to anyone looking to improve their impact assessment. MICS uses 200 variables to determine the impact of a citizen-science project in five areas: society, the environment, the economy, governance, and science and technology. Five case studies explore how citizen scientists work together to monitor nature-based solutions and protect the environment. AI technology has been developed to help analyse the 200 variables.

2022-01-01T00:00:00Z https://repository.oceanbestpractices.org/handle/11329/2419 2024-01-17T16:32:31Z 2020-01-01T00:00:00Z

ECSA's Characteristics of Citizen Science. Version 1. This document attempts to represent a wide range of opinions in an inclusive way, to allow for different types of projects and programmes, where context-specific criteria can be set.The characteristics outlined below are based on views expressed by researchers, practitioners, public officials and the wider public. Our aim is to identify the characteristics that should be considered when setting such criteria (e.g. a funding scheme), and we call upon readers to determine which subset of these characteristics is relevant to their own specific context and aims. These characteristics build on (and refer to) the ECSA 10 principles of citizen science as a summary of best practie – and projects are expected to engage meaningfully with them. Where it is especially pertinent, we refer to them in the characteristics below. The rest of the document covers the characteristics of citizen science under five sections: (1) core concepts; (2) disciplinary aspects; (3) leadership and participation; (4) financial aspects; and (5) data and knowledge. Further explanation and background are provided in the ‘ECSA’s characteristics of citizen science: explanation notes’ document. The research article describing this work 'Contours of citizen science: a vignette study' can be found in the Royal Society Open Science journal at https://doi.org/10.1098/rsos.202108.

2020-01-01T00:00:00Z Golumbic, Yaela N. Oesterheld, Marius https://repository.oceanbestpractices.org/handle/11329/2411 2024-01-15T12:52:56Z 2023-01-01T00:00:00Z

From goals to engagement— evaluating citizen science project descriptions as science communication texts. Golumbic, Yaela N.; Oesterheld, Marius Introduction: Attracting and recruiting volunteers is a key aspect of managing a citizen science initiative. Science communication plays a central role in this process. In this context, project descriptions are of particular importance, as they are very often, the first point of contact between a project and prospective participants. As such, they need to be reader-friendly, accessible, spark interest, contain practical information, and motivate readers to join the project. Methods: This study examines citizen science project descriptions as science communication texts. We conducted a thorough review and analysis of a random sample of 120 English-language project descriptions to investigate the quality and comprehensiveness of citizen science project descriptions and the extent to which they contain information relevant to prospect participants. Results: Our findings reveal information deficiencies and challenges relating to clarity and accessibility. While goals and expected outcomes were frequently addressed, practical matters and aspects related to volunteer and community management were much less well-represented. Discussion: This study contributes to a deeper understanding of citizen science communication methods and provides valuable insights and recommendations for enhancing the effectiveness and impact of citizen science.

2023-01-01T00:00:00Z Guribye, Eugene Iversen, Lisbeth https://repository.oceanbestpractices.org/handle/11329/2313 2023-07-14T20:39:45Z 2020-01-01T00:00:00Z

Methods and tools for Citizen Participation and Co-Creation. Guribye, Eugene; Iversen, Lisbeth This document presents a selection of 40 tools or methodologies for citizen involvement in the form of meeting places, participation in planning processes, dialogue through digital tools, knowledge acquisition and new approaches to mobilize volunteers and promote engagement. We have also roughly listed different financial models for collaboration processes. The document is part of Arendal municipality’s project “Samskaping i Arendal” (Co-creation in Arendal) funded by the County Governor of Agder County. The descriptions in this memo are not intended to be guides on how participation and co-creation should be carried out, but be used as inspiration for possible opportunities in the work of citizen participation. References to relevant websites, booklets, manuals etc., as well as available research are provided. It is encouraged to test out new methodologies as listed below, and seek more information on how these can be implemented.

2020-01-01T00:00:00Z Kosmala, Margaret Wiggins, Andrea Swanson, Alexandra Simmons, Brooke https://repository.oceanbestpractices.org/handle/11329/2155 2024-01-12T15:39:43Z 2016-01-01T00:00:00Z

Assessing data quality in citizen science. Kosmala, Margaret; Wiggins, Andrea; Swanson, Alexandra; Simmons, Brooke Ecological and environmental citizen-science projects have enormous potential to advance scientific knowledge, influence policy, and guide resource management by producing datasets that would otherwise be infeasible to generate. However, this potential can only be realized if the datasets are of high quality. While scientists are often skeptical of the ability of unpaid volunteers to produce accurate datasets, a growing body of publications clearly shows that diverse types of citizen-science projects can produce data with accuracy equal to or surpassing that of professionals. Successful projects rely on a suite of methods to boost data accuracy and account for bias, including iterative project development, volunteer training and testing, expert validation, replication across volunteers, and statistical modeling of systematic error. Each citizen-science dataset should therefore be judged individually, according to project design and application, and not assumed to be substandard simply because volunteers generated it.

2016-01-01T00:00:00Z https://repository.oceanbestpractices.org/handle/11329/2029 2022-07-21T15:27:13Z 2021-01-01T00:00:00Z

Guidelines for collecting citizen observations on non-indigenous species (NIS). Monitoring of non-indigenous species (NIS) is required through several international agreements and guidelines, such as the EU Regulation on Invasive Alien Species (The European Parliament and the Council of the European Union 2014), European Union (EU) Biodiversity Strategy (European Commission 2011) and Marine Strategy Framework Directive (MSFD) of the EU (European Parliament Council 2008). However, most countries do not have governmental monitoring programs targeting the presence and abundance of NIS (Lehtiniemi et al. 2015), even though NIS monitoring is required by international legislations and is of great importance to national environmental management. Monitoring programs can be costly and often spatially and temporally limited (Delaney et al. 2008). Citizen observations can therefore improve the monitoring efforts by increasing the number of potential observers and therefore number of observations. Citizen observations are particularly useful in detecting seasonally occurring events, such as migration patterns, blooming events and areal ice thickness (Lovett et al. 2007; Tulloch et al. 2013; Kettunen et al. 2016), as well as new NIS, since public members have often been the first to discover new species (Lodge et al. 2006). In terms of aquatic NIS, citizen science (e.g. fishermen, beach goers, recreational boaters) can be a very useful tool in monitoring range expansion of invasive species (Lehtiniemi et al. In press). Citizens usually are not using harmonized sampling methods and are often unequally spatially and temporally distributed. Observations cannot therefore replace more rigorous monitoring programs. Also, as citizen observations tend to produce presence only-type data, it may have limitations for use (e.g. for modelling). Furthermore, species that citizens can observe are usually macroscopic, easy to identify due to distinguishing features or they form mass blooms that attract attention (sensu Fitzpatrick et al. 2009). Hence, microscopic or cryptic species are not usually observed. Despite of these caveats, citizen observations can supplement monitoring programs in detecting NIS and add important insights of ranges of especially charismatic species with small cost and effort. These guidelines aim to describe creating a citizen science platform to collect citizen observations of NIS (see example in www.vieraslajit.fi, Figure 1). The data collected can be used in the assessment of the HELCOM core indicator ‘Trends in arrival of non-indigenous species’ as well as in national reporting. Furthermore, citizen science platform can be utilized to raise awareness among local citizens about non-indigenous species and creating alerts of species that may potentially be invading into the area.

2021-01-01T00:00:00Z De Rijck, Kim Schade, Sven Rubio, Jose-Miguel Van Meerloo, Marjan https://repository.oceanbestpractices.org/handle/11329/1980 2024-01-12T15:40:38Z 2020-01-01T00:00:00Z

Best Practices in Citizen Science for Environmental Monitoring: Commission Staff Working Document. De Rijck, Kim; Schade, Sven; Rubio, Jose-Miguel; Van Meerloo, Marjan The volume of environmental knowledge generated by citizen science initiatives across the EU offers a unique opportunity to help deliver on the European Green Deal and other EU (and global) priorities, and to involve the public in EU policy-making. This document summarises the opportunities for and benefits of using citizen science for environmental monitoring, highlights good practices and lessons learnt, and identifies the obstacles holding back its broader uptake. On that basis, it puts forward recommendations and possible actions to facilitate and enhance the use of citizen science in environmental monitoring.

2020-01-01T00:00:00Z Langenkamper, Daniel Simon-Lledo, Erik Hosking, Brett Jones, Daniel O. B. Nattkemper, Tim W. https://repository.oceanbestpractices.org/handle/11329/1907 2024-01-12T16:13:06Z 2019-01-01T00:00:00Z

On the impact of Citizen Science-derived data quality on deep learning based classification in marine images. Langenkamper, Daniel; Simon-Lledo, Erik; Hosking, Brett; Jones, Daniel O. B.; Nattkemper, Tim W. The evaluation of large amounts of digital image data is of growing importance for biology, including for the exploration and monitoring of marine habitats. However, only a tiny percentage of the image data collected is evaluated by marine biologists who manually interpret and annotate the image contents, which can be slow and laborious. In order to overcome the bottleneck in image annotation, two strategies are increasingly proposed: “citizen science” and “machine learning”. In this study, we investigated how the combination of citizen science, to detect objects, and machine learning, to classify megafauna, could be used to automate annotation of underwater images. For this purpose, multiple large data sets of citizen science annotations with different degrees of common errors and inaccuracies observed in citizen science data were simulated by modifying “gold standard” annotations done by an experienced marine biologist. The parameters of the simulation were determined on the basis of two citizen science experiments. It allowed us to analyze the relationship between the outcome of a citizen science study and the quality of the classifications of a deep learning megafauna classifier. The results show great potential for combining citizen science with machine learning, provided that the participants are informed precisely about the annotation protocol. Inaccuracies in the position of the annotation had the most substantial influence on the classification accuracy, whereas the size of the marking and false positive detections had a smaller influence.

2019-01-01T00:00:00Z Pucino, Nicolas Kennedy, David M. Carvalho, Rafael C. Allan, Blake Ierodiaconou, Daniel https://repository.oceanbestpractices.org/handle/11329/1901 2024-01-12T15:59:41Z 2021-01-01T00:00:00Z

Citizen science for monitoring seasonal‑scale beach erosion and behaviour with aerial drones. Pucino, Nicolas; Kennedy, David M.; Carvalho, Rafael C.; Allan, Blake; Ierodiaconou, Daniel Sandy beaches are highly dynamic systems which provide natural protection from the impact of waves to coastal communities. With coastal erosion hazards predicted to increase globally, data to inform decision making on erosion mitigation and adaptation strategies is becoming critical. However, multitemporal topographic data over wide geographical areas is expensive and time consuming and often requires highly trained professionals. In this study we demonstrate a novel approach combining citizen science with low-cost unmanned aerial vehicles that reliably produces survey-grade morphological data able to model sediment dynamics from event to annual scales. The high-energy wave-dominated coast of south-eastern Australia, in Victoria, is used as a field laboratory to test the reliability of our protocol and develop a set of indices to study multi-scale erosional dynamics. We found that citizen scientists provide unbiased data as accurate as professional researchers. We then observed that open-ocean beaches mobilise three times as much sediment as embayed beaches and distinguished between slowed and accelerated erosional modes. The data was also able to assess the efficiency of sand nourishment for shore protection. Our citizen science protocol provides high quality monitoring capabilities, which although subject to important legislative preconditions, it is applicable in other parts of the world and transferable to other landscape systems where the understanding of sediment dynamics is critical for management of natural or anthropogenic processes.

2021-01-01T00:00:00Z