The collection of biodiversity data is possible by non-professionals and this is part of a not-canonical and interdisciplinary approach on scientific research called “citizen science”. One of the most important factors which accelerated the development of citizen science in the last decade has been the use of mobile devices which incorporate sensors. The smartphone is one of these devices for the possibility of catching pictures and register a number of information (mainly date, hour, geographic position). In this context, the data provided by a community of citizens can be used for testing scientific hypothesis or developing experiments.

iNaturalist is a nonprofit social network of citizen scientists developed to share biodiversity observations and currently it is the fourth largest data provider to the Global Biodiversity Information Facility (GBIF - www.gbif.org/). Through it, users can collect, organize, map, and share biodiversity observations across the globe.

In this study, we used the iNaturalist platform to assess the impact of the data collected within the LTER-Italy umbrella project (www.inaturalist.org/projects/lter-italy-network), which means that all observations recorded within the boundaries of LTER-Italy sites, according to the Dynamic Ecological Information Management System - Site and Dataset Registry (DEIMS-SDR) (see Table 1, Fig. 1 and Fig. 2 step A), are automatically collected under the project. Our analysis aimed to evaluate how the data generated thorough the iNaturalist platform contribute to scientific research within the LTER-Italy sites, including their relevance, usability, and integration into the broader goals of the network.

Figure 1.  

Observations on selected LTER sites as of November 20, 2024. Colors indicate observations registered in the different sites.

Figure 2.  

Flowchart describing the procedure implemented for extracting and enriching the dataset used for the analysis.

Fig. 1

We explored the contribution of iNaturalist to:

1. an increase in the number of observations of species of conservation concern,
2. facilitate the detection of species previously un-recorded in the area,
3. evaluate the presence of red-listed or non-native species,
4. offer insights for new research lines,
5. provide data for Standard Observations (SOs) (e.g., flying insects, vegetation composition, acoustic recording) (Zacharias 2024).

Additionally, we evaluated the efficiency of iNaturalist across different ecosystems (terrestrial, freshwater, marine, and transitional) and examined whether the data collected via iNaturalist differed significantly from those recorded by researchers.

To ensure a robust dataset for our analysis, we included in the present study LTER-Italy sites with more than 100 iNaturalist observations. As of November 20, 2024, the date on which the selection was made, 26 out of 78 LTER-Italy research sites met this threshold (Table 1).

We then carried out, via the built-in query module integrated in the iNaturalist web portal, a selection of the observations that had been validated by other users and had achieved the status of "Verifiable Observation", meeting the criteria of having a valid date, a geographic location, a photo or sound, and not involving captive or cultivated organisms. Among them we further selected observations classified as "Research Grade," that had received at least two independent identification confirmations (Table 1). After the selection process, our dataset includes only observations that are georeferenced, taxonomically labeled, fully verifiable, and highly reliable (Fig. 2 step B1). Thanks to using GIS software, we were able to overlay the observations with areas with specific management designations - such as integral reserves - to assess whether observations fell within these protected zones. With this operation we have thus been able to enrich observation incorporating information on the habitat, ecosystem and conservation status of the area where the observation was recorded (Fig. 2 step B2).

To complete the quality control and enrichment process, based on the taxon, we assigned each observation a label related to: the conservation status, based on the IUCN Red List (www.iucnredlist.org), and the degree of nativeness, based on the national list of non-native species (Fig. 2, step C). Comprehensive observation lists and maps related to the number and distribution of non-native species and those in a high state of vulnerability (Critically Endangered, Endangered, and Vulnerable), were then created for each site (Fig. 2 step D, Fig. 3).

Figure 3.  

Map of georeferenced observations collected within the LTER-Italy Tenuta di Castelporziano site (deims.org/0d2269d3-5423-4939-a30d-077c8bc38b03).

Below, we summarize some preliminary results from our analysis:

1. most observations were conducted in lake and terrestrial ecosystems (67%), indicating that the use of iNaturalist is more widespread and effective in these environments;
2. 40% of the observations are related to SOs, including Flying Insects (16%), Vegetation Composition (21%), and Acoustic Recordings (3%).

Additionally, we highlighted three examples of sites that could help in addressing our initial research questions:

1. at Val Mazia/Matschertal, iNaturalist observations shared with the Natural History Museum of Bolzano led to the discovery of four new spider species in the Province of Bolzano, two of which were previously unknown in Italy (Steinwandter et al. 2022);
2. at Foce Trigno - Marina di Petacciato (Abruzzo-Molise) and Foce Saccione - Bonifica Ramitelli (Molise), the “Wild Coast CASCADE” iNaturalist project, launched by the University of Molise, combined citizen science observations with traditional research data, helping to detect red-listed and non-native species (Compagnone et al. 2023);
3. at Castelporziano (Lazio), iNaturalist observations collected during events like bioblitzes could be used into ongoing biodiversity research projects in the area.

standard observations, essential variables, big data, data interoperability, semantic web, AI, modelling, digital twins, cross-disciplinary approach

Alexander Palummo

ORAL