How to inventory tropical flies (Diptera)—One of the megadiverse orders of insects
Bibliographic record
Abstract
A new approach to inventory Diptera species in tropical habitats is described. A 150 x 266 m patch of cloud forest at Zurquí de Moravia, Costa Rica (10.047N, 84.008W) at 1585 meters asl was sampled with two Malaise traps for slightly more than one year (Sept. 12, 2012-Oct. 18, 2013). Further concomitant sampling with a variety of trapping methods for three days every month and collecting during a one-week intensive "Diptera Blitz", with 19 collaborators collecting on-site, provided diverse additional samples used in the inventory. Two other Costa Rican sites at Tapantí National Park (9.720N, 83.774W, 1600 m) and Las Alturas (8.951N, 82.834W, 1540 m), 40 and 180 km southeast from Zurquí de Moravia, respectively, were each sampled with a single Malaise trap to allow for beta-diversity assessments. Tapantí National Park was sampled from Oct. 28, 2012-Oct. 13, 2013 and Las Alturas from Oct. 13, 2012-Oct. 13, 2013. A worldwide group of 54 expert systematists are identifying to species level all 72 dipteran families present in the trap samples. Five local technicians sampled and prepared material to the highest curatorial standards, ensuring that collaborator efforts were focused on species identification. This project, currently in its final, third year of operation (to end Sept. 1, 2015), has already recorded 2,348 species and with many more yet expected. Unlike previous All Taxon Biodiversity Inventories, this project has attainable goals and will provide the first complete estimate of species richness for one of the four megadiverse insect orders in a tropical region. Considering that this is the first complete survey of one of the largest orders of insects within any tropical region of the planet, there is clearly great need for a consistent and feasible protocol for sampling the smaller but markedly more diverse smaller insects in such ecosystems. By weight of their species diversity and remarkable divergence of habit, the Diptera are an excellent model to gauge microhabitat diversity within such systems. Our model appears to be the first to provide a protocol that can realistically be expected to provide a portrayal of the true species diversity of a megadiverse order of insects in the tropics.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.010 |
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 source (direct Gemma or distilled Codex), 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".