More than a Bit of Fun: The Multiple Outcomes of a Bioblitz

ParasiteBlitz: Adaptation of the BioBlitz concept to parasitology

A BioBlitz is a rapid and intensive survey of a specific geographic area that brings together experts and often lay participants to assess biodiversity, typically of macrobiota that are easily observed and identifiable on-site. This concept has become popular across taxonomic fields, attracting interest globally to increase knowledge of local biodiversity. Inspired by the success of the approach, we undertook a 'ParasiteBlitz' at an unexplored locality (Stono Preserve, Charleston, South Carolina, USA) to determine its feasibility for parasites, whose assessment of diversity is largely neglected worldwide. We assembled a team of parasitologists with complementary expertise. Over 12 days (3 days in each habitat) in April 2023, we intensively screened fishes and aquatic invertebrates for parasites, and sampled sediment and water for environmental DNA (eDNA) metabarcoding from four aquatic habitats: wetland, freshwater pond, brackish impoundment, and tidal creek. We incorporated assistance from non-parasitologists and students. Details on methodologies and results are provided in individual papers in this Special Collection. Traditional methods revealed the presence of ca. 100 species of seven major metazoan parasite taxa, and the eDNA survey yielded over 1,000 amplicon sequence variants identified as parasites, most with sequences unmatched in GenBank, and resulting in only a few species identified as named species in the one-year post-Blitz timeframe we imposed upon ourselves for identification. Limitations and challenges of the ParasiteBlitz are discussed, and our results support that this approach can be effective for rapid discovery of the dimensions of parasite assemblages in an understudied environment and contribute to parasitology knowledge.

Emerging technologies in citizen science and potential for insect monitoring

Emerging technologies are increasingly employed in environmental citizen science projects. This integration offers benefits and opportunities for scientists and participants alike. Citizen science can support large-scale, long-term monitoring of species occurrences, behaviour and interactions. At the same time, technologies can foster participant engagement, regardless of pre-existing taxonomic expertise or experience, and permit new types of data to be collected. Yet, technologies may also create challenges by potentially increasing financial costs, necessitating technological expertise or demanding training of participants. Technology could also reduce people's direct involvement and engagement with nature. In this perspective, we discuss how current technologies have spurred an increase in citizen science projects and how the implementation of emerging technologies in citizen science may enhance scientific impact and public engagement. We show how technology can act as (i) a facilitator of current citizen science and monitoring efforts, (ii) an enabler of new research opportunities, and (iii) a transformer of science, policy and public participation, but could also become (iv) an inhibitor of participation, equity and scientific rigour. Technology is developing fast and promises to provide many exciting opportunities for citizen science and insect monitoring, but while we seize these opportunities, we must remain vigilant against potential risks. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

Using citizen science data for predicting the timing of ecological phenomena across regions

The scarcity of long-term observational data has limited the use of statistical or machine-learning techniques for predicting intraannual ecological variation. However, time-stamped citizen-science observation records, supported by media data such as photographs, are increasingly available. In the present article, we present a novel framework based on the concept of relative phenological niche, using machine-learning algorithms to model observation records as a temporal sample of environmental conditions in which the represented ecological phenomenon occurs. Our approach accurately predicts the temporal dynamics of ecological events across large geographical scales and is robust to temporal bias in recording effort. These results highlight the vast potential of citizen-science observation data to predict ecological phenomena across space, including in near real time. The framework is also easily applicable for ecologists and practitioners already using machine-learning and statistics-based predictive approaches.

Citizen science initiatives document biodiversity baselines at an urban lake

Changes to biodiversity from urbanization are occurring worldwide, and baseline data is vital to document the magnitude and direction of these alterations. We set out to document the biodiversity of an urban lake in Eastern Iowa that was devoid of baseline data prior to a renovation project that will convert the site into a major area for human recreation. Throughout the course of one year, we studied the biodiversity at Cedar Lake utilizing the citizen-science application iNaturalist coupled with semi-structured BioBlitz events, which we compared to previous opportunistic observations at the site. From a semi-structured approach to document biodiversity with citizen science, our analyses revealed more diverse community metrics over a shorter period compared to more than a decade of prior observations.

Citizen science is a vital partnership for invasive alien species management and research

Invasive alien species (IAS) adversely impact biodiversity, ecosystem functions, and socio-economics. Citizen science can be an effective tool for IAS surveillance, management, and research, providing large datasets over wide spatial extents and long time periods, with public participants generating knowledge that supports action. We demonstrate how citizen science has contributed knowledge across the biological invasion process, especially for early detection and distribution mapping. However, we recommend that citizen science could be used more for assessing impacts and evaluating the success of IAS management. Citizen science does have limitations, and we explore solutions to two key challenges: ensuring data accuracy and dealing with uneven spatial coverage of potential recorders (which limits the dataset's "fit for purpose"). Greater co-development of citizen science with public stakeholders will help us better realize its potential across the biological invasion process and across ecosystems globally while meeting the needs of participants, local communities, scientists, and decision-makers.