Climate change contributes to widespread declines among bumble bees across continents - DATA REPOSITORY
Bibliographic record
Abstract
Data and code repository for Soroye et al. 2020. (DOI: 10.1126/science.aax8591)Gridded environmental observations and R scripts used to process data and generate all results from study. The bumblebee dataset has been previously used in Kerr et al 2015, and contains data assembled from a variety of sources including (Polce et al 2018, Rasmont et al 2015, Potts et al 2015, and Williams et al 2014), and other sources listed in the complete acknowledgement below. This data is provided in accordance with the Research Standards and data policies of Science, to allow any researchers to reproduce or extend the analysis. Researchers wishing to use these data for novel applications or questions should first seek permission from the original data providers (see complete acknowledgement below for a list). J. T. Kerr, A. Pindar, P. Galpern, L. Packer, S. G. Potts, S. M. Roberts, P. Rasmont, O. Schweiger, S. R. Colla, L. L. Richardson, D. L. Wagner, L. F. Gall, D. S. Sikes, A. Pantoja, Climate change impacts on bumblebees converge across continents. Science 349, 177–180 (2015). doi:10.1126/science.aaa7031 C. Polce, J. Maes, X. Rotllan-Puig, D. Michez, L. Castro, B. Cederberg, L. Dvorak, Ú.Fitzpatrick, F. Francis, J. Neumayer, A. Manino, J. Paukkunen, T. Pawlikowski, S. Roberts, J. Straka, P. Rasmont, Distribution of bumblebees across europe. One Ecosyst. 3, e28143 (2018). doi:10.3897/oneeco.3.e28143S. G. Potts, J. C. Biesmeijer, R. Bommarco, A. Felicioli, M. Fischer, P. Jokinen, D. Kleijn,A.-M. Klein, W. E. Kunin, P. Neumann, L. D. Penev, T. Petanidou, P. Rasmont, S. P. M. Roberts, H. G. Smith, P. B. Sørensen, I. Steffan-Dewenter, B. E. Vaissière, M. Vilà, A. Vujić, M. Woyciechowski, M. Zobel, J. Settele, O. Schweiger, Developing European conservation and mitigation tools for pollination services: Approaches of the STEP (Status and Trends of European Pollinators) project. J. Apic. Res. 50, 152–164 (2015). doi:10.3896/IBRA.1.50.2.07P. H. Williams, R. W. Thorp, L. L. Richardson, S. R. Colla, Bumble Bees of North America:An Identification Guide (Princeton Univ. Press, 2014).P. Rasmont, M. Franzen, T. Lecocq, A. Harpke, S. Roberts, K. Biesmeijer, L. Castro, B.Cederberg, L. Dvorak, U. Fitzpatrick, Y. Gonseth, E. Haubruge, G. Mahe, A. Manino, D. Michez, J. Neumayer, F. Odegaard, J. Paukkunen, T. Pawlikowski, S. Potts, M. Reemer,J. Settele, J. Straka, O. Schweiger, Climatic Risk and Distribution Atlas of European Bumblebees. BioRisk 10, 1–236 (2015). doi:10.3897/biorisk.10.4749 The authors would like to thank all contributors to the bumble bee dataset, and the tireless hours of those who helped put it together, especially Alana Pindar, Paul Galpern, Laurence Packer, Simon G. Potts, Stuart M. Roberts, Pierre Rasmont, Oliver Schweiger, Sheila R. Colla, Leif L. Richardson, David L. Wagner, Lawrence F. Gall, Derek S. Sikes, and Alberto Pantoja. We are grateful to data contributors from North America: Bee Biology and Systematics Lab, USDA-ARS, Utah State University; John Ascher, National University of Singapore and American Museum of Natural History, New York, USA; Doug Yanega, University of California, Riverside (NSF-DBI #0956388 and #0956340), California, USA; Illinois Natural History Survey, Illinois, USA; Packer Lab Research Collection, York University, Canada; Canadian National Collection, Agriculture and Agri-Food Canada; Canada; Peabody Museum, Yale University; Sam Droege, USGS Patuxent Wildlife Research Center, USA; Boulder Museum of Natural History, University of Colorado, Colorado, USA. From Europe: Status and Trends of European Pollinators (STEP) Collaborative Project (grant 244090, www.STEP-project.net); Bees, Wasps and Ants Recording Society; BDFGM Banque de Données Fauniques (P. Rasmont & E. Haubruge); BWARS (UK, S.P.M. Roberts); SSIC (Sweden, B. Cederberg); Austria (J. Neumayer); EISN (Netherland, M. Reemer); CSCF (Suisse, Y. Gonseth); Poland (T. Pawlikowski); NBDC (Eire, U. FitzPatrick); FMNH (Finland, J. Paukkunen); Czech Republic (J. Straka, L. Dvorak); France (G. Mahé); NSIC (Norway, F. Odegaard); UK (S.P.M. Roberts); Italy (A. Manino); Spain (L. Castro) Global Biodiversity Information Facility (GBIF), http://gbif.org for records from North America and Europe.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.170 | 0.068 |
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".