Inconspicuous taxa in citizen science-based botanical research: actual contribution, limitations, and new opportunities for non-vascular cryptogams
Bibliographic record
Abstract
Citizen science (CS) has gathered an impressive wealth of open biodiversity data over the last decade, with demonstrated significant scientific contributions in biology and conservation science. However, the contribution of CS in botanical research, and more particularly regarding inconspicuous taxonomic groups such as cryptogams remains largely unexplored. Here we assess the current status and contribution of CS in botanical research, with a special focus on non-vascular “cryptogams” (bryophytes, lichens, fungi, and algae). We conducted a literature review for the period 2012 to 2022 to synthesize the use of CS in botanical studies. We found an increasing trend in the use of CS for botanical research (average annual increase of ∼40%), although highly biased towards vascular plants (246 papers). Cryptogams remained strongly underrepresented (58 papers), although receiving slightly growing attention since 2018. The inconspicuousness nature, high diversity, challenges with species identification, and low public perception of cryptogams not only restrict the contribution made by non-experts but raise concerns about the reliability and robustness of generated data. This is fueled by the scarcity of foundational methodological studies in cryptogams, which seems to undermine the scientific confidence in engaging volunteers for their research or using open data from CS platforms and tools. Despite this, our review showed a gradual adoption of CS approaches for cryptogam research, which is particularly led by mycologists. We highlight the versatility and potential of CS approaches for advancing cryptogam knowledge across various research subjects at spatial and temporal scales otherwise unfathomable by researchers, and provide insights on the opportunities of application and possible solutions to the discussed limitations. We hope our work motivates mycologists, phycologists, bryologists, and lichenologists to further embrace CS, and increase public awareness on these highly sensitive and ecologically important taxa.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.008 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".