Trends and gaps in the use of citizen science derived data as input for species distribution models: A quantitative review

Abstract

Citizen science (CS) currently refers to the participation of non-scientist volunteers in any discipline of conventional scientific research. Over the last two decades, nature-based CS has flourished due to innovative technology, novel devices, and widespread digital platforms used to collect and classify species occurrence data. For scientists, CS offers a low-cost approach of collecting species occurrence information at large spatial scales that otherwise would be prohibitively expensive. We examined the trends and gaps linked to the use of CS as a source of data for species distribution models (SDMs), in order to propose guidelines and highlight solutions. We conducted a quantitative literature review of 207 peer-reviewed articles to measure how the representation of different taxa, regions, and data types have changed in SDM publications since the 2010s. Our review shows that the number of papers using CS for SDMs has increased at approximately double the rate of the overall number of SDM papers. However, disparities in taxonomic and geographic coverage remain in studies using CS. Western Europe and North America were the regions with the most coverage (73%). Papers on birds (49%) and mammals (19.3%) outnumbered other taxa. Among invertebrates, flying insects including Lepidoptera, Odonata and Hymenoptera received the most attention. Discrepancies between research interest and availability of data were as especially important for amphibians, reptiles and fishes. Compared to studies on animal taxa, papers on plants using CS data remain rare. Although the aims and scope of papers are diverse, species conservation remained the central theme of SDM using CS data. We present examples of the use of CS and highlight recommendations to motivate further research, such as combining multiple data sources and promoting local and traditional knowledge. We hope our findings will strengthen citizen-researchers partnerships to better inform SDMs, especially for less-studied taxa and regions. Researchers stand to benefit from the large quantity of data available from CS sources to improve global predictions of species distributions.

National‐scale predictions of plant assemblages via community distribution models: Leveraging published data to guide future surveys

“…Sesleria albicans-Galium sterneri calcarious grassland (Figure S1), U17 Luzula sylvatica-Geum rivale tall-herb community (Figure 4) and M17 Scirpus cespitosus-Eriophorum vaginatum blanket mire (Figure S11) were all predicted with relatively high accuracy (TSS 0.820 or above). All three contain plant species included in the national Red Data List for vascular plants (Stroh et al, 2014) (Feldman et al, 2021) and while biases may arise due to spatial variation in collection efforts or taxonomic skill (Robinson et al, 2018) there is evidence that they can provide an invaluable resource for applied ecologists with both pre-processing to ensure data quality (Isaac et al, 2014) Of key importance is that the plant species that volunteers are asked to focus on were derived from the weighted occurrence of species within the NVC system, so as to be representative of each community, while at the same time avoiding species that would be taxonomically challenging for amateur botanists. This is termed the 'wildflower level' of participation to minimise identification errors (Pescott et al, 2015).…”

Biodiversity Research in Central America: A Regional Comparison in Scientific Production Using Bibliometrics and Democracy Indicators

“…Our data set for studying biodiversity science production in the region was based on the use of Bio-Dem as a platform that is fed solely by the data presented in the GBIF, and the V-Dem research project. There are other initiatives of citizen science platforms that could be taken into consideration, especially in regards to species records (Feldman et al, 2021 ). Our bibliometric analysis had some limitations that are worth pointing out.…”

“…This tool allowed us to explore the relationship between Central American species occurrence records from the Global Biodiversity Information Facility (GBIF) ( www.gbif.org ) and the region's political framework from the Varieties of Democracy (V-Dem) database ( www.v-dem.net ) from 1960 to 2020 (Coppedge, 2020 ; Zizka et al, 2021 ). Geo-referenced species occurrence records deposited in GBIF have become crucial for biodiversity research and data modeling (Feldman et al, 2021 ), while V-Dem is the world's largest database dedicated to the collection and conceptualization of democracy data (Coppedge, 2020 ).…”

Conservation Status of Milkcaps (Basidiomycota, Russulales, Russulaceae), with Notes on Poorly Known Species

“…Focusing on little more than 100 species of Basidiomycota (no milkcaps, though), Ascomycota, rusts and lichens, LAFF resulted in a dataset of over 1500 records of 77 species, some of which (e.g., Godronia fuliginosa and Sporomega degenerans) have been rediscovered after a recording gap of over 50 years. Notwithstanding these virtuous examples, a recent analysis of the use of citizen science as a source of data for species distribution models has revealed "a notable under-use of plant, fungi, lichen and bryophyte public databases in the last decade in papers that model the distribution of species, as compared to the interest that they generate in CS [citizen science] programs", a fact attributed by authors to the difficulty of identifying species of these taxonomic groups in the field [90]. For what concerns macrofungi, the best success stories mentioned above have clearly indicated that a strict collaboration between professional and amateur mycologists is paramount in order to build reliable datasets, to be used as a robust basis for conservation mycology initiatives (even iNaturalist has 'identifiers').…”