Global knowledge and use of soil biodiversity: Results of an expert survey
Bibliographic record
Abstract
A global survey on soil biodiversity was conducted over a three week period in March 2022 by the Global Soil Partnership (GSP) of the Food and Agriculture Organization (FAO) of the United Nations, as part of the activities of the International Network on Soil Biodiversity (NETSOB). The survey intended to obtain information on the current status of knowledge and use of soil organisms worldwide, i.e., to identify who is doing what, where, and how, as well as the main gaps, pitfalls, and opportunities across existing national initiatives and research. It included 122 questions that characterized the work undertaken by experts regarding microbes, fauna, and their activity in soils, community & functional assessments, inventories, mapping and monitoring activities, ecosystem services, applications, and threats to soil biodiversity, education, and communication activities, as well as public policies related to soil biodiversity. The online survey was created using the software Survey Monkey v. 11 and was sent out to over 70 thousand e-mail addresses with a link to complete the survey. Over 2,600 responses were received, representing >1,350 institutions from 135 countries, mainly from experts active in research and academia. The number of respondents was not equal for all questions, as the survey guided the respondents to different parts, depending on their replies. The 122 questions and the replies of the respondents are presented as separate tabs in the Excel file. The respondents and their identities, as well as their e-mails and any personal websites were removed in the current file to maintain anonymity. Institutional websites were maintained as long as they did not identify the respondent(s) directly. A detailed written description of the survey results was prepared as a manuscript for the journal Soil Organisms (Brown et al., submitted), while a condensed version with a selection of the results was sent to the journal Science (Parnell et al., submitted). The survey was prepared by a team of scientists from the Brazilian Corporation for Agricultural Research (Embrapa) and collaborating institutions, with assistance from the board of the International Network on Soil Biodiversity (NETSOB), and with funding provided by the FAO, and supported by the Fundação de Apoio a Pesquisa e Desenvolvimento Agropecuário Edmundo Gastal (FAPEG), Brazil.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".