A protocol for reproducible functional diversity analyses
Bibliographic record
Abstract
The widespread use of species traits to infer community assembly mechanisms or to link species to ecosystem functions has led to an exponential increase in functional diversity analyses, with >10,000 papers published in 2010–2019, and >1,500 papers only in 2020. This interest is reflected in the development of a multitude of theoretical and methodological frameworks for calculating functional diversity, making it challenging to navigate the myriads of options and to report details to reproduce a trait-based analysis. Therefore, the study of functional diversity would benefit from the existence of a general guideline for standard reporting and good practices in this discipline. We do so by streamlining available terminology, concepts, and methods, with the overarching goal of increasing reproducibility, transparency and comparability across studies. The protocol is based on the following key elements: identification of a research question, a sampling scheme and a study design, assemblage of community and trait data matrices, data exploration and preprocessing, functional diversity computation, model fitting, evaluation and interpretation, and data, metadata and code provision. Throughout the protocol, we provide information on how to best select research questions and study designs, and discuss ways to ensure reproducibility in reporting results. To facilitate the implementation of this protocol, we further developed an interactive web-based application (stepFD) in the form of a checklist workflow, detailing all the steps of the protocol and providing tabular and graphical outputs that can be merged to produce a final report. The protocol streamlined here is expected to promote the description of functional diversity analyses in sufficient detail to ensure full transparency and reproducibility. A thorough reporting of functional diversity analyses ensures that ecologists can incorporate others’ findings into meta-analyses, the shared data can be integrated into larger databases for consensus analyses, and available code can be reused by other researchers. All these elements are key to push forward this vibrant and fast-growing field of research.
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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 | 0.058 | 0.113 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.239 | 0.103 |
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".